Multi-Class and Single-Class Classification Approaches to Vehicle Model Recognition from Im

一些常见的统计术语翻译Absolute deviation, 绝对离差Absolute number , 绝对数Absolute r esiduals, 绝对残差Acceler ation arr ay, 加速度立体阵Acceler ation in an arbitr ary dir ection, 任意方向上的加速度Acceler ation nor mal, 法向加速度Acceler ation spac e dimension, 加速度空间的维数Acceler ation tangential, 切向加速度Acceler ation vector , 加速度向量Acceptable hypothesis, 可接受假设Accum ulation, 累积Accuracy, 准确度Actual fr equency, 实际频数Adaptive estimator , 自适应估计量Addition, 相加Addition theor em , 加法定理Additivity, 可加性Adjusted r ate, 调整率Adjusted value, 校正值Adm issible error , 容许误差Aggregation, 聚集性Alternative hypothesis, 备择假设Among gr oups, 组间Amounts, 总量Analysis of c orr elation, 相关分析Analysis of c ovarianc e, 协方差分析Analysis of r egr ession, 回归分析Analysis of time series, 时间序列分析Analysis of varianc e, 方差分析Angular tr ansfor mation, 角转换ANOVA (analysis of variance ), 方差分析ANOVA Models, 方差分析模型Arcing, 弧/ 弧旋Arcsine tr ansfor mation, 反正弦变换Area under the curve, 曲线面积AREG , 评估从一个时间点到下一个时间点回归相关时的误差ARIMA, 季节和非季节性单变量模型的极大似然估计Arithmetic grid paper , 算术格纸Arithmetic mean, 算术平均数Arrhenius r elation, 艾恩尼斯关系Assessing fit, 拟合的评估Associative laws, 结合律Asymmetric distribution, 非对称分布Asymptotic bias, 渐近偏倚Asymptotic efficiency, 渐近效率Asymptotic variance, 渐近方差Attributable risk, 归因危险度Attribute data, 属性资料Attribution, 属性Autoc orrelation, 自相关Autoc orrelation of residuals, 残差的自相关Aver age, 平均数Aver age c onfidenc e interval length, 平均置信区间长度Aver age growth r ate, 平均增长率Bar c hart, 条形图Bar gr aph, 条形图Base period, 基期Bayes' theorem , Bayes 定理Bell-shaped curve, 钟形曲线伯努力分布Ber noulli distribution,Best-trim estimator , 最好切尾估计量Bias, 偏性Binary logistic r egr ession, 二元逻辑斯蒂回归Binomial distribution, 二项分布Bisquare, 双平方Bivariate Corr elate, 二变量相关Bivariate nor mal distribution, 双变量正态分布Bivariate nor mal population, 双变量正态总体Biweight inter val, 双权区间Biweight M-estimator, 双权M 估计量Bloc k, 区组/ 配伍组BMDP(Biomedic al computer pr ograms), BMDP 统计软件包Boxplots, 箱线图/ 箱尾图Breakdown bound, 崩溃界/ 崩溃点Canonical c orrelation, 典型相关Caption, 纵标目Case-c ontrol study , 病例对照研究Categoric al variable, 分类变量Catenary, 悬链线Cauchy distribution, 柯西分布Cause-and-effect r elationship, 因果关系Cell, 单元Censoring, 终检Center of symmetry , 对称中心Centering and sc aling, 中心化和定标Centr al tendency, 集中趋势Centr al value, 中心值CHAID - x 2 Automatic Inter action Detector ,卡方自动交互检测Chanc e, 机遇Chanc e error , 随机误差Chanc e variable, 随机变量Char acteristic equation, 特征方程Char acteristic root, 特征根Char acteristic vector , 特征向量Chebshev criterion of fit, 拟合的切比雪夫准则Chernoff fac es, 切尔诺夫脸谱图Chi-square test, 卡方检验/咒2检验Choleskey dec omposition, 乔洛斯基分解Circle chart, 圆图Class interval, 组距Class mid-value, 组中值Class upper limit, 组上限Classified variable, 分类变量Cluster analysis, 聚类分析Cluster sampling, 整群抽样Code, 代码Coded data, 编码数据Coding, 编码Coefficient of c ontingency, 列联系数Coefficient of deter mination, 决定系数Coefficient of multiple c orr elation, 多重相关系数Coefficient of partial c orrelation, 偏相关系数Coefficient of pr oduction-moment c orrelation, 积差相关系数Coefficient of r ank corr elation, 等级相关系数Coefficient of r egr ession, 回归系数Coefficient of skewness, 偏度系数Coefficient of variation, 变异系数Cohort study, 队列研究Column, 列Column effect, 列效应Column factor , 列因素Combination pool, 合并Combinative table, 组合表Common factor , 共性因子Common regr ession coefficient, 公共回归系数Common value, 共同值Common varianc e, 公共方差Common variation, 公共变异Communality varianc e, 共性方差Compar ability, 可比性Comparison of bathes, 批比较Comparison value, 比较值Compartment model, 分部模型Compassion, 伸缩Complement of an event, 补事件Complete association, 完全正相关Complete dissociation, 完全不相关Complete statistic s, 完备统计量Completely r andomized design, 完全随机化设计Composite event, 联合事件Composite events, 复合事件Concavity, 凹性Conditional expectation, 条件期望Conditional likelihood, 条件似然Conditional pr obability, 条件概率Conditionally linear , 依条件线性Confidenc e interval, 置信区间Confidenc e lim it, 置信限Confidenc e lower lim it, 置信下限Confidenc e upper limit, 置信上限Confir matory Factor Analysis , 验证性因子分析Confir matory research, 证实性实验研究Confounding factor , 混杂因素Conjoint, 联合分析Consistency, 相合性Consistency chec k, 一致性检验Consistent asymptotic ally nor mal estimate, 相合渐近正态估计Consistent estimate, 相合估计Constr ained nonlinear r egr ession, 受约束非线性回归Constr aint, 约束Contam inated distribution, 污染分布Contam inated Gausssian, 污染高斯分布Contam inated nor mal distribution, 污染正态分布Contam ination, 污染Contam ination model, 污染模型Contingency table, 列联表Contour , 边界线Contribution r ate, 贡献率Control, 对照Controlled experiments, 对照实验Conventional depth, 常规深度Convolution, 卷积Corrected factor , 校正因子Corrected mean, 校正均值Correction coefficient, 校正系数Correctness, 正确性Correlation c oefficient, 相关系数Correlation index, 相关指数Correspondenc e, 对应Counting, 计数Counts, 计数/ 频数Covarianc e, 协方差Covariant, 共变Cox Regression, Cox 回归Criteria for fitting, 拟合准则Criteria of least squar es, 最小二乘准则Critic al r atio, 临界比Critic al r egion, 拒绝域Critic al value, 临界值Cr oss-over design, 交叉设计Cr oss-section analysis, 横断面分析Cr oss-section survey, 横断面调查Cr osstabs , 交叉表Cr oss-tabulation table, 复合表Cube r oot, 立方根Cumulative distribution function, 分布函数Cumulative probability, 累计概率Curvatur e, 曲率/ 弯曲Curvatur e, 曲率Curve fit , 曲线拟和Curve fitting, 曲线拟合Curvilinear r egression, 曲线回归Curvilinear r elation, 曲线关系Cut-and-try method, 尝试法Cycle, 周期Cyclist, 周期性D test, D 检验Data acquisition, 资料收集Data bank, 数据库Data c apacity, 数据容量Data deficiencies, 数据缺乏Data handling, 数据处理Data manipulation, 数据处理Data proc essing, 数据处理Data r eduction, 数据缩减Data set, 数据集Data sourc es, 数据来源Data tr ansfor mation, 数据变换Data validity, 数据有效性Data-in, 数据输入Data-out, 数据输出Dead time, 停滞期Degr ee of fr eedom, 自由度Degr ee of pr ecision, 精密度Degr ee of r eliability , 可靠性程度Degr ession, 递减Density function, 密度函数Density of data points,数据点的密度Dependent variable,应变量/ 依变量/ 因变量Dependent variable,因变量Depth, 深度Derivative matrix, 导数矩阵Derivative-fr ee methods, 无导数方法Design, 设计Deter minacy, 确定性Deter minant, 行列式Deter minant, 决定因素Deviation, 离差Deviation from aver age, 离均差Diagnostic plot, 诊断图Dichotomous variable, 二分变量Differential equation,微分方程Direct standardization, 直接标准化法Discr ete variable, 离散型变量DISCRIMINAN T, 判断Discriminant analysis, 判别分析Discriminant c oeffic ient, 判别系数Discriminant function, 判别值Disper sion, 散布/ 分散度Dispr oportional, 不成比例的Dispr oportionate sub-class numbers, 不成比例次级组含量Distribution free, 分布无关性/ 免分布Distribution shape, 分布形状Distribution-free method, 任意分布法Distributive laws, 分配律Distur banc e, 随机扰动项Dose response curve, 剂量反应曲线Double blind method, 双盲法Double blind trial, 双盲试验Double exponential distribution, 双指数分布Double logarithmic, 双对数Downward r ank, 降秩Dual-spac e plot, 对偶空间图DUD, 无导数方法新法Duncan's new multiple r ange method, 新复极差法/DuncanE-LEffect, 实验效应Eigenvalue, 特征值Eigenvector , 特征向量Ellipse, 椭圆Empiric al distribution, 经验分布Empiric al pr obability , 经验概率单位Enumer ation data, 计数资料Equal sun-class number , 相等次级组含量Equally likely , 等可能Equivarianc e, 同变性Error , 误差/ 错误Errorof estimate, 估计误差Error type I, 第一类错误Error type II, 第二类错误Estimand, 被估量Estimated err or mean squares, 估计误差均方Estimated err or sum of squar es, 估计误差平方和Euclidean distanc e,欧式距离Event, 事件Event, 事件Exc eptional data point, 异常数据点Expectation plane, 期望平面Expectation surfac e, 期望曲面Expected values, 期望值Experiment, 实验Experimental sampling, 试验抽样Experimental unit, 试验单位Explanatory variable, 说明变量Explor atory data analysis, 探索性数据分析Explore Summarize, 探索- 摘要Exponential curve, 指数曲线Exponential growth, 指数式增长EXSMOOTH, 指数平滑方法Extended fit, 扩充拟合Extr a par ameter ,附加参数Extr apolation, 外推法Extr eme observation, 末端观测值Extr emes, 极端值/ 极值F distribution, F分布 F test, F 检验Factor , 因素 / 因子Factor analysis, 因子分析Factor Analysis, 因子分析Factor scor e, 因子得分Factorial, 阶乘Factorial design, 析因试验设计False negative, 假阴性False negative error , 假阴性错误 Fam ily of distributions, 分布族 Fam ily of estimator s, 估计量族 Fanning, 扇面Fatality r ate, 病死率Field investigation, 现场调查Field survey , 现场调查Finite population, 有限总体 Finite-sample, 有限样本First derivative, 一阶导数First principal component,First quartile, 第一四分位数Fisher infor mation, 费雪信息量Fitted value, 拟合值Fourth, 四分点Frequency, 频率Frontier point, 界限点Function r elationship, 泛函关系Gaussian distribution, 高斯分布 / 正态分布Gini's mean difference,基尼均差 GLM (Gener al liner models), 通用线性模型Fitting a c urve, 曲线拟合 Fixed base,定基 Fluctuation, 随机起伏 For ec ast, 预测 Four fold table,四格表Fraction blow, 左侧比率Fractional error, 相对误差 Frequency polygon,频数多边图 Gamma distribution, 伽玛分布Gauss increment, 高斯增量Gauss-Newton incr ement, 高斯- 牛顿增量 Gener al census, 全面普查GENLOG (Gener alized liner models), 广义线性模型 Geometric mean,几何平均数 第一主成分Goodness of fit, 拟和优度/ 配合度Gradient of deter m inant, 行列式的梯度Graec o-Latin squar e, 希腊拉丁方Grand mean, 总均值Gross error s, 重大错误Gross-error sensitivity, 大错敏感度Group aver ages, 分组平均Grouped data, 分组资料Guessed mean, 假定平均数Half-life, 半衰期Hampel M-estimators, 汉佩尔M 估计量Happenstanc e, 偶然事件Har monic mean, 调和均数Hazar d function, 风险均数Hazar d r ate, 风险率Heading, 标目Heavy-tailed distribution, 重尾分布Hessian arr ay, 海森立体阵Heterogeneity , 不同质Heterogeneity of variance, 方差不齐Hier archic al classific ation, 组内分组Hier archic al clustering method, 系统聚类法High-lever age point, 高杠杆率点HILOGLINEAR, 多维列联表的层次对数线性模型Hinge, 折叶点Histogr am, 直方图Historical c ohort study, 历史性队列研究Holes, 空洞HOMALS, 多重响应分析Homogeneity of varianc e, 方差齐性Homogeneity test, 齐性检验Huber M-estimators, 休伯M 估计量Hyper bola, 双曲线Hypothesis testing, 假设检验Hypothetic al universe, 假设总体Impossible event, 不可能事件Independenc e, 独立性Independent variable, 自变量Index, 指标/ 指数Indir ect standardization, 间接标准化法Individual, 个体Infer enc e band, 推断带Infinite population, 无限总体Infinitely gr eat, 无穷大Infinitely small, 无穷小Influence curve, 影响曲线Intercept, 截距Interpolation, 内插法Invarianc e, 不变性Inverse matrix, 逆矩阵Inverse sine tr ansfor mation, 反正弦变换Iter ation, 迭代Jac obian deter m inant, 雅可比行列式Joint distribution function,分布函数 Joint probability, 联合概率Joint probability distribution,联合概率分布 K means method, 逐步聚类法Kaplan-Meier , 评估事件的时间长度Kaplan-Merier c hart, Kaplan-Merier图 Kendall's r ank c orrelation, Kendall等级相关 Kinetic, 动力学Kolmogor ov-Smirnove test, 柯尔莫哥洛夫 - 斯米尔诺夫检验Kruskal and Wallis test, Kr uskal 及 Wallis 检验 / 多样本的秩和检验 /H 检验 Kurtosis, 峰度Lac k of fit, 失拟Ladder of powers, 幂阶梯Lag, 滞后Lar ge sample, 大样本Lar ge sample test, 大样本检验Latin squar e, 拉丁方Latin squar e design, 拉丁方设计Leakage, 泄漏Least favor able c onfigur ation, 最不利构形Least favor able distribution, 最不利分布Least signific ant differ enc e, 最小显著差法Least squar e method, 最小二乘法Least-absolute-r esiduals estimates, Least-absolute-r esiduals fit, 最小绝对残差拟合 Least-absolute-r esiduals line, 最小绝对残差线 Legend, 图例L-estimator , L 估计量Infor mation capacity, 信息容量 Initial condition,初始条件 Initial estimate,初始估计值 Initial level,最初水平 Interaction,交互作用 Interaction terms, 交互作用项Interquartile range,四分位距 Interval estimation,区间估计 Intervals of equal probability, 等概率区间 Intrinsic c urvature,固有曲率Inverse probability,逆概率最小绝对残差估计L-estimator of loc ation, 位置L 估计量L-estimator of sc ale, 尺度L 估计量Level, 水平Life expectanc e, 预期期望寿命Life table, 寿命表Life table method, 生命表法Light-tailed distribution, 轻尾分布似然函数Likelihood function,似然比Likelihood r atio,line gr aph, 线图直线相关Linear corr elation,线性方程Linear equation,Linear pr ogr amm ing, 线性规划直线回归Linear regr ession,线性回归Linear Regression,Linear trend, 线性趋势Loading, 载荷Loc ation and sc ale equivarianc e, 位置尺度同变性Loc ation equivarianc e, 位置同变性Loc ation invarianc e, 位置不变性Loc ation sc ale family, 位置尺度族Log r ank test, 时序检验Logarithm ic curve, 对数曲线Logarithm ic nor mal distribution, 对数正态分布Logarithm ic sc ale, 对数尺度Logarithm ic tr ansfor mation, 对数变换Logic chec k, 逻辑检查Logistic distribution, 逻辑斯特分布Logit tr ansfor mation, Logit 转换LOGLINEAR, 多维列联表通用模型Lognor mal distribution, 对数正态分布Lost function, 损失函数Low corr elation, 低度相关Lower lim it, 下限Lowest-attained varianc e, 最小可达方差LSD, 最小显著差法的简称Lur king variable, 潜在变量M-RMain effect, 主效应Major heading, 主辞标目Marginal density function, 边缘密度函数Marginal pr obability, 边缘概率Marginal pr obability distribution, 边缘概率分布Matched data, 配对资料Matched distribution, 匹配过分布Matching of distribution, 分布的匹配Matching of tr ansfor mation, 变换的匹配Mathematic al expectation, 数学期望Mathematic al model, 数学模型Maximum L-estimator , 极大极小L 估计量Maximum likelihood method, 最大似然法Mean, 均数Mean squar es between groups, 组间均方Mean squar es within gr oup, 组内均方Means (Compar e means), 均值- 均值比较Median, 中位数Median effective dose, 半数效量Median lethal dose, 半数致死量Median polish, 中位数平滑Median test, 中位数检验Minimal sufficient statistic, 最小充分统计量Minimum distanc e estimation, 最小距离估计Minimum effective dose, 最小有效量Minimum lethal dose, 最小致死量Minimum varianc e estimator , 最小方差估计量MIN ITAB, 统计软件包Minor heading, 宾词标目Missing data, 缺失值Model specific ation, 模型的确定Modeling Statistic s , 模型统计Models for outliers, 离群值模型Modifying the model, 模型的修正Modulus of c ontinuity , 连续性模Mor bidity , 发病率Most favor able c onfigur ation, 最有利构形Multidimensional Sc aling (ASCAL), 多维尺度/ 多维标度Multinomial Logistic Regression , 多项逻辑斯蒂回归Multiple c omparison, 多重比较Multiple c orr elation , 复相关Multiple c ovarianc e, 多元协方差Multiple linear r egr ession, 多元线性回归Multiple r esponse , 多重选项Multiple solutions, 多解Multiplic ation theor em , 乘法定理Multir esponse, 多元响应Multi-stage sampling, 多阶段抽样Multivariate T distribution, 多元T 分布Mutual exclusive, 互不相容Mutual independenc e, 互相独立Natur al boundary, 自然边界Natur al dead, 自然死亡Natur al zer o, 自然零Negative c orr elation, 负相关Negative linear corr elation, 负线性相关Negatively skew ed, 负偏Newman-Keuls method, q 检验NK method, q 检验No statistic al signific ance, 无统计意义Nom inal variable, 名义变量Nonc onstancy of variability, 变异的非定常性Nonlinear regr ession, 非线性相关Nonpar ametric statistics, 非参数统计Nonpar ametric test, 非参数检验Nonpar ametric tests, 非参数检验Normal deviate, 正态离差Normal distribution, 正态分布Normal equation, 正规方程组Normal r anges, 正常范围Normal value, 正常值Nuisanc e par ameter , 多余参数/ 讨厌参数Null hypothesis, 无效假设Numeric al variable, 数值变量Objective function, 目标函数观察单位Observation unit,观察值Observed value,One sided test, 单侧检验One-way analysis of varianc e, 单因素方差分析Oneway ANOVA , 单因素方差分析Open sequential trial, 开放型序贯设计Optrim, 优切尾Optrim efficiency, 优切尾效率Order statistic s, 顺序统计量Or dered categories, 有序分类Or dinal logistic r egr ession , 序数逻辑斯蒂回归有序变量Or dinal variable,正交基Orthogonal basis,Orthogonal design, 正交试验设计Orthogonality c onditions, 正交条件ORTHOPLAN, 正交设计Outlier cutoffs, 离群值截断点Outlier s, 极端值OVE RALS , 多组变量的非线性正规相关Over shoot, 迭代过度Pair ed design, 配对设计Pair ed sample, 配对样本Pairwise slopes, 成对斜率Par abola, 抛物线Par allel tests, 平行试验Par ameter , 参数Par ametric statistic s, 参数统计Par ametric test, 参数检验Partial c orrelation, 偏相关Partial r egression, 偏回归Partial sorting, 偏排序Partials r esiduals, 偏残差Patter n, 模式Pear son curves, 皮尔逊曲线Peeling, 退层Perc ent bar gr aph, 百分条形图Perc entage, 百分比Perc entile, 百分位数Perc entile curves, 百分位曲线Periodicity , 周期性Per mutation, 排列P-estimator , P 估计量Pie graph, 饼图Pitman estimator , 皮特曼估计量Pivot, 枢轴量Planar , 平坦Planar assumption, 平面的假设PLANCARDS, 生成试验的计划卡Point estimation, 点估计Poisson distribution, 泊松分布Polishing, 平滑Polled standar d deviation, 合并标准差Polled varianc e, 合并方差Polygon, 多边图Polynomial, 多项式Polynomial c urve, 多项式曲线Population, 总体Population attributable risk,人群归因危险度Qualitative classific ation, 属性分类Qualitative method, 定性方法Quantile-quantile plot, Quantitative analysis, Quartile, 四分位数Quic k Cluster , 快速聚类Radix sort, 基数排序Random alloc ation, 随机化分组Random bloc ks design, 随机区组设计Random event, 随机事件Random ization, 随机化Range, 极差/ 全距Rank c orr elation, 等级相关Rank sum test, 秩和检验Rank test, 秩检验 Ranked data, 等级资料Rate, 比率Ratio, 比例 Positive c orrelation, 正相关Positively skewed, 正偏Posterior distribution, 后验分布Power of a test, 检验效能 Precision,精密度Predicted value, 预测值Preliminary analysis, 预备性分析Principal c omponent analysis, 主成分分析Prior distribution, 先验分布 Prior pr obability, Probabilistic model, probability, 概率Probability density Product moment, 先验概率概率模型, 概率密度 乘积矩 / 协方差Profile tr ace, 截面迹图Proportion, 比/ 构成比Proportion alloc ation in str atified random sampling, Proportionate, 成比例Proportionate sub-class numbers, 成比例次级组含量Prospective study , 前瞻性调查Proximities, 亲近性Pseudo F test, 近似 F 检验Pseudo model, 近似模型Pseudosigma, 伪标准差Purposive sampling, 有目的抽样QR dec omposition, QR 分解Quadratic approximation, 二次近似 按比例分层随机抽样分位数-分位数图 /Q-Q 图 定量分析Raw data, 原始资料Raw residual, 原始残差Rayleigh's test, 雷氏检验Rayleigh's Z, 雷氏Z 值Recipr ocal, 倒数Recipr ocal tr ansfor mation, 倒数变换Rec or ding, 记录Redesc ending estimators, 回降估计量Reducing dimensions, 降维Re-expression, 重新表达Refer enc e set, 标准组Region of acc eptanc e, 接受域Regr ession coefficient, 回归系数Regr ession sum of squar e, 回归平方和Rej ection point, 拒绝点Relative disper sion, 相对离散度Relative number , 相对数Reliability , 可靠性Repar ametrization, 重新设置参数Replication, 重复Report Summar ies, 报告摘要Residual sum of squar e, 剩余平方和Resistanc e, 耐抗性Resistant line, 耐抗线Resistant technique, 耐抗技术R-estimator of location, 位置R 估计量R-estimator of sc ale, 尺度R 估计量Retr ospective study, 回顾性调查Ridge tr ace, 岭迹Ridit analysis, Ridit 分析Rotation, 旋转Rounding, 舍入Row, 行Row effects, 行效应Row factor , 行因素RXC table, RXC 表S-ZSample, 样本Sample r egression c oefficient, 样本回归系数Sample size, 样本量Sample standar d deviation, 样本标准差Sampling error , 抽样误差SAS(Statistical analysis system ), SAS Scale, 尺度/ 量表Scatter diagr am, 散点图统计软件包Schematic plot, 示意图/ 简图Scor e test, 计分检验Screening, 筛检SEASON, 季节分析Sec ond derivative, 二阶导数Sec ond principal c omponent, 第二主成分SEM (Structur al equation modeling), 结构化方程模型Semi-logarithm ic gr aph, 半对数图Semi-logarithm ic paper , 半对数格纸Sensitivity c urve, 敏感度曲线Sequential analysis,贯序分析Sequential data set, 顺序数据集Sequential design, 贯序设计Sequential method, 贯序法Sequential test, 贯序检验法Serial tests, 系列试验Short-c ut method, 简捷法Sigmoid curve, S形曲线Sign function, 正负号函数Sign test, 符号检验Signed r ank, 符号秩Signific anc e test, 显著性检验Signific ant figur e, 有效数字Sim ple cluster sampling, 简单整群抽样Sim ple c orrelation, 简单相关Sim ple r andom sampling, 简单随机抽样Sim ple r egr ession, 简单回归simple table, 简单表Sine estimator , 正弦估计量Single-valued estimate, 单值估计Singular matrix, 奇异矩阵Skewed distribution, 偏斜分布Skewness, 偏度Slash distribution, 斜线分布Slope, 斜率Smirnov test, 斯米尔诺夫检验Source of variation, 变异来源Spear man r ank c orrelation, 斯皮尔曼等级相关Specific factor , 特殊因子Specific factor varianc e, 特殊因子方差Spectr a , 频谱Spherical distribution, 球型正态分布Spr ead, 展布SPSS(Statistical pac kage for the social scienc e), SPSS Spurious c orr elation, 假性相关Square root tr ansfor mation, 平方根变换Stabilizing variance, 稳定方差Standard deviation, 标准差Standard error , 标准误Standard error of differ ence, 差别的标准误Standard error of estimate, 标准估计误差Standard error of r ate, 率的标准误Standard nor mal distribution, 标准正态分布Standardization, 标准化Starting value, 起始值Statistic, 统计量Statistical c ontrol, 统计控制Statistical gr aph, 统计图Statistical inferenc e, 统计推断Statistical table, 统计表Steepest desc ent, 最速下降法Stem and leaf display, 茎叶图Step factor , 步长因子Stepwise r egr ession, 逐步回归Stor age, 存Strata, 层(复数)Stratified sampling, 分层抽样Stratified sampling, 分层抽样Strength, 强度Stringency , 严密性Structur al r elationship, 结构关系Studentized r esidual, 学生化残差/t 化残差Sub-class number s, 次级组含量Subdividing, 分割Sufficient statistic, 充分统计量Sum of pr oducts, 积和Sum of squares, 离差平方和Sur e event, 必然事件Survey, 调查Survival, 生存分析统计软件包Sum of squares about regr Sum of squares between gr Sum of squares of partial r ession, 回归平方和oups, 组间平方和egression, 偏回归平方和Survival r ate, 生存率Suspended r oot gr am, 悬吊根图Symmetry, 对称Systematic err or, 系统误差Systematic sampling, 系统抽样Tags, 标签Tail ar ea, 尾部面积Tail length, 尾长Tail weight, 尾重Tangent line, 切线Target distribution, 目标分布Taylor series, 泰勒级数Tendency of dispersion, 离散趋势Testing of hypotheses, 假设检验Theor etical frequency , 理论频数Time series, 时间序列Toler anc e interval, 容忍区间Toler anc e lower lim it, 容忍下限Toler anc e upper lim it, 容忍上限Torsion, 扰率Total sum of squar e, 总平方和Total variation, 总变异Transfor mation, 转换Treatment, 处理Trend, 趋势Trend of perc entage, 百分比趋势Trial, 试验Trial and err or method, 试错法Tuning c onstant, 细调常数Two sided test, 双向检验Two-stage least squar es, 二阶最小平方Two-stage sampling, 二阶段抽样Two-tailed test, 双侧检验Two-way analysis of varianc e, 双因素方差分析Two-way table, 双向表Type I err or, 一类错误/ a错误Type II err or,二类错误/ B错误UMVU, 方差一致最小无偏估计简称Unbiased estimate, 无偏估计Unc onstrained nonlinear r egr ession , 无约束非线性回归Unequal subclass number , 不等次级组含量Ungr ouped data, 不分组资料Unifor m coor dinate, 均匀坐标Unifor m distribution, 均匀分布Unifor m ly m inimum varianc e unbiased estimate, 方差一致最小无偏估计Unit, 单元Unor der ed categories, 无序分类Upper lim it, 上限Upwar d r ank, 升秩Vague conc ept, 模糊概念Validity , 有效性W test, W 检验W-estimation, W 估计量W-estimation of location,位置 W 估计量Width, 宽度 Wilcoxon paired test, 威斯康星配对法 / 配对符号秩和检验 Wild point, 野点 / 狂点Wild value, 野值 / 狂值Winsorized mean, 缩尾均值Withdr aw, 失访Youden's index, 尤登指数Z test, Z 检验Zer o corr elation, 零相关Z-tr ansfor mation, Z 变换 VARCOMP (Varianc e c omponent estimation), 方差元素估计 Variability , 变异性 Variable,变量 Varianc e,方差 Variation, 变异Varimax orthogonal rotation, 方差最大正交旋转 Volume of distribution,容积Weibull distribution, 威布尔分布 Weight, 权数Weighted Chi-squar e test, 加权卡方检验 /Coc hr an 检验 Weighted linear regression method, 加权直线回归 Weighted mean, 加权平均数Weighted mean squar Weighted sum of squarWeighting coefficient,Weighting method,e, 加权平均方差e, 加权平方和 权重系数 加权法。

Traffic Classification Approach Based on Support Vector Machine and Statistic Signature Seonhwan Hwang1, Keuchul Cho1, Junhyung Kim1, Youngmi Baek1,Jeongbae Yun1, and Kijun Han21 The Graduate School of Electrical Engineering and Computer Science,Kyungpook National University, 1370, Sankyuk-dong, Buk-gu, Daegu, 702-701, Korea {shhwang,k5435n,jhkim,maya,jbyun}@netopia.knu.ac.kr2 The School of Computer Science and Engineering, Kyungpook National University, 1370,Sankyuk-dong, Buk-gu, Daegu, 702-701, Korea************.krAbstract. As network traffic is dramatically increasing, classification ofapplication traffic becomes important for the effective use of network resources.Classification of network traffic using port-based or payload-based analysis isbecoming increasingly difficult because of many peer-to-peer (P2P)applications using dynamic port numbers, masquerading techniques, andencryption. An alternative approach is to classify traffic by exploiting thedistinctive characteristics of applications. In this paper, we propose aclassification method of application traffic using statistic signatures based onSVM (Support Vector Machine). The statistic signatures, defined as adirectional sequence of packet size in a flow, are collected for each application,and applications are classified by SVM mechanism.Keywords: Traffic, Application, Classification, Statistic Signature, SupportVector Machine.1IntroductionTraffic classification plays an important role in common network management applications, such as intrusion detection and network monitoring. However, it is challenging to classify the applications associated with network connections according to their various characteristics and behaviors [1].Former researches have proposed a number of methods to identify the application associated with a traffic flow. Port-based methods by examining TCP port numbers are simple because many well-known applications have specific port numbers assigned by IANA. However, the port-based classification is insufficient [2, 3, 4, 5], mainly because many applications use dynamic port-negotiation mechanisms to hide from firewalls and network security tools. Another approach is to inspect the payload of every packet. However, this approach has several problems. First, this method cannot be used if the payload is encrypted. Second, there are privacy concerns with examining user data. Third, there is a high storage and computational cost to study every packet that traverses a link.S. Balandin et al. (Eds.): NEW2AN/ruSMART 2013, LNCS 8121, pp. 332–339, 2013.© Springer-Verlag Berlin Heidelberg 2013Traffic Classification Approach Based on SVM and Statistic Signature 333 To address these challenges, we propose a classification method of application traffic using SVM that only uses the size of the first few data packets of each connection.The remainder of the paper is organized as follows. In Section 2, we describe related works. Section 3 presents our classification method that uses static signature based on SVM. Performance evaluation and discussion are given in Section 4. Section 5 proposes concludes the paper.2Related WorksBernaille et al [1, 6] suggested traffic classification based on packet header trace technique, known as "on the fly" classification. They only utilized the first 5 significant packets (in both directions) of a TCP connection to classify, based on clustering. Usually, the packet header gives more information without inspecting payload. Their approach allows the unsupervised online classification of traffic, and therefore allows actions to be taken during the connections. They employed data clustering using only the sizes and directions of the first 5 packets. The direction is used as the signal (first and same-direction packets: positive; opposite direction packets: negative). By ignoring TCP handshake packets and ACKs with no payload, the clustering of only 5 packets allows the online classification of flows with a considerable hit ratio.Support Vector Machine (SVM) developed by Vapnik in 1995 is a classification and regression prediction tool that uses machine learning theory to maximize predictive accuracy while automatically avoiding over-fit to the data. Fig. 1 shows an example of SVM using linear classifiers which could separate the data into two groups.MarginOptimal hyperplaneH1H2X1X2Fig. 1. An example of Support Vector Machine using linear classifier334 S. Hwang et al.3Our Classification MethodIn this section, we present our classification method that uses static signature based on SVM. Our classification mechanism works in two phases: SVM data set training phase and traffic classification phase as shown in Fig. 2. The training phase obtains models of application behaviors. The trace contains a representative sample of flow from all target applications. The classification phase associates a new flow with an application by using the group defined in the training phase.Fig. 2. Two Phases for Traffic Classification3.1Flow TraceThe flow traces are the input for the SVM. Flow is defined as a collection of both directional packets of 5-tuple information (source IP, destination IP, source port, destination port, protocol). We only use the size of the data packets, not using TCP control packets (SYN, Ack with no data, etc.). We analyze the trace and convert each flow into a spatial representation based on the size of its first N packets. Flow data set is generated by the size for the first N packets of each flow. Only one application is executed for collecting packet by the application. Flow trace server collects the first N packets of connection by the application.Traffic Classification Approach Based on SVM and Statistic Signature 335 3.2Packet ConversionThe conversion module extracts the flow and the packet size. Statistic signature is made into vector which consists of payload size and direction of application packet. The analyzer filters out control traffic (the three packets of the TCP handshake) and stores the size of every packet in both directions of the connection. When it knows the size for the first N packets of the flow, it sends this information to the assignment module which associates the flow based on application descriptions.Fig. 3. SVM signature using the size of packet payloadFig. 3 presents SVM database by the size of packet payload. Classification ID is whole number by application classification. Other fields composed the first N packet payload size by flow. And the database has enough statistics signature per application. Direction is represented by positive and negative, positive value represents sent packet from the client to the server, and negative from server to client in case of TCP. But, Because UDP classification is neither one thing nor the other, meaning of positive/negative is indicated to only the opposite direction. In UDP, the first packet is positive. And the second packet will be positive if it is the same direction. If not, it will be negative.3.3SVM TrainingIn our scheme, we use multi-class SVM for classifying many applications at the same time. In addition, we use Radial Basis Function (RBF) of non-linear way which is more accurate than liner classification. Fig. 4(a) presents an example of payload distribution by the first 2 packets of Nateon and uTorrent. After finishing the packet conversion phase, different application is divided to hyperplane at SVM training phase. Fig. 4(b) presents grouping result of two application distributions shown in Fig. 4(a) by RBF way.336 S. Hwang et al. -1500-1000-500050010001500-1500-5005001500T h e s i z e o f t h e s e c o n d p a c k e t The size of the first packet Nateon uTorrent (a) Payload distribution of Nateonand uTorrent.(b) Two groups classified by SVM RBF. Fig. 4. An example of application classification by SVM3.4 Traffic ClassificationIn traffic classification phase, we collect packet of various applications. The classifying module determines which application is most likely associated with the flow. Connection of each application is classified by multi-class SVM.4 SimulationsWe carried out simulations using statistic signature classification by SVM. All packets of simulation environment were generated by executing application in the test-bed. We used maximum 10-dimension vector for SVM training in simulation. In the simulation, we used 3 programs: Wireshark ver. 1.8.3 (Packet capture), C++ ver. 2008 (Signature conversion) and SVMmulticlass ver. 2.20 (Training & classification). Also, we used 3 types of kernel function in SVM: linear, radial basis function, sigmoid. Table 1 shows the number of applications and signatures, and Table 2 presents application list and type.Table 1. Coverage of SVM classificationApplication Training signature Classification signature Coverage 5 5,1984,482Table 2. Application listType Application nameMessenger NateonWebhard WebhardP2P uTorrentGame League Of Legends(LOL)Encrypted packet SSHTraffic Classification Approach Based on SVM and Statistic Signature 337 Fig. 5, 6, 7, and 8 present the accuracy of our classifier using the first N packets of each flow by sigmoid, linear and RBF of multi-class SVM. Fig. 5 indicated that SVM sigmoid can only classify application packets of Nateon and LOL, but it is not appropriate to classify packets of Webhard, uTorrent and SSH, since the sigmoid classifier is not a good model to fit straight lines for traffic with similar packet size.Fig. 5. Accuracy of SVM sigmoid classificationFig. 6 indicated that when we use first 2 packets for signature capturing, the SVM linear can only classify application packets of Nateon and Webhard. It is not appropriate to use the SVM linear classifier to separate packets of uTorrent, LOL and SSH. And when we use first 3~4 packets, the SVM linear classifier can roughly distinguish application packets of Nateon, uTorrent and SSH. We can see that the linear classifier is not a good model to discriminate traffic with similar packet size.Fig. 6. Accuracy of SVM linear classification338 S. Hwang et al.Fig. 7 indicated that the SVM RBF classifier can successfully classify all 5 types of traffic. In special, it was shown that we could get very accurate results with the first 2~5 packets. Bu, the classification accuracy drops with more than 5 packets. This is because the packet size is different depending on the user application environments. It means when network applications communicate with each other, there is no significant difference in the packet size if less than 5 packets are used. After the fifth packet, the packet size becomes drastically different according to the operation of application.Fig. 7. Accuracy of SVM RBF classificationFig. 8 shows the average accuracy of SVM RBF, linear, and sigmoid classifications. From this graph, we can see that the classification using RBF has the highest accuracy.Fig. 8. Average accuracy of SVM RBF, linear, and sigmoid classificationsTraffic Classification Approach Based on SVM and Statistic Signature 339 5ConclusionsIn this letter, we proposed a traffic classification scheme by using only payload size and direction of application packet without examining TCP port numbers and inspecting the payload of every packet. Our classification mechanism works in two phases: SVM data set training phase and traffic classification phase. The training phase obtains models of application behaviors. The trace contains a representative sample of flow from all target applications. We apply SVM techniques to a set of training data to group flows. The classification phase associates a new flow with an application by using the group defined in the training phase.We evaluate three different classifier methods in SVM: sigmoid, linear and RBF. Simulation results showed that the RBF classifier can successfully classify 5 types of application traffic from Nateon and LOL, Webhard, uTorrent, and SSH, with the first 2~5 packets.Acknowledgements. This work was supported by the IT R&D program of MOTIE/KEIT. [10041145, Self-Organized Software platform(SoSp) for Welfare Devices].This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2011-0029034).References1.Bernaille, L., Teixeira, R., Akodkenou, I., Soule, A., Salamantian, K.: TrafficClassification On The Fly. ACM SIGCOMM Computer Communication Review 36(2), 23–26 (2006)2.Karagiannis, T., Broido, A., Brownlee, N., Claffy, K., Faloutsos, M.: Is P2P dying or justhiding? In: IEEE Globecom (2004)3.Roughan, M., Sen, S., Spatscheck, O., Duffield, N.: Class-of-service mapping for QoS: Astatistical signature-based approach to IP traffic classification. In: Internet Measurement Conference (2004)4.Moore, A., Zuev, D.: Internet traffic classification using bayesian analysis. In: ACMSIGMETRICS (2005)5.Karagiannis, T., Papagiannaki, D., Faloutsos, M.: BLINC: Multilevel traffic classificationin the dark. In: ACM SIGCOMM (2005)6.Bernaille, L., Teixeira, R., Salamantian, K.: Early Application Identification. In: SecondConference on Future Networking Technologies (December 2006)7.Callado, A., Kamienski, C., Szabó, G., Gerő, B.P., Kelner, J., Fernandes, S., Sadok, D.: ASurvey on Internet Traffic Identification. IEEE Communications Surveys & Tutorials 11(3) (Third quarter 2009)8.Vapnik, V.: The Nature of Statistical Learning Theory. Springer, NewYork (1995)。

集成电路设计与集成系统专业本科培养计划Undergraduate Program for Specialty in IC Design and Integrated System一、培养目标Ⅰ．Educational Objectives以集成电路及各类电子信息系统设计为目标，培养掌握集成电路基本理论、基本方法及EDA 工具，能在集成电路及系统集成相关领域从事科研、教学、科技开发、工程技术、生产管理与行政管理等工作的高级专门人才。

Targeted to design integrated circuit and all sorts of electronic information systems, t his program aims at training advanced talents who can grasp fundamental integrated circuit theories, methods and EDA tools. These talents can meet the demands of scientific research, education, technique development, engineering technology, production management and administration management for the integrated circuit and system and its related fields.二、基本规格要求Ⅱ．Skills Profile要求学生具有良好素质、道德修养和创新能力，具备扎实的数学、物理、外语基础，掌握大规模集成电路及集成系统所必需的基本理论和方法，具有超大规模集成电路分析及设计、版图设计和系统集成等的基本能力。

具体而言，毕业生应获得以下几个方面的知识和能力：1. 具有较扎实的自然科学基本理论基础和宽阔的科学视野；2. 对全球信息科学和技术的前沿、发展动态及其影响具有足够的理解力和敏感性；3. 具备较强的分析问题和解决问题的综合应用能力；4. 具有较强的外语和计算机应用能力；5. 掌握文献检索、资料查询的方法和撰写科学论文的能力；6. 具有良好的人文素质、有效的交际能力以及较强的协调、组织能力；7. 具有较强的创新精神和竞争意识；8. 具有较强的在未来生活和工作中继续学习的能力。

DatasheetUACC-OM-MM-10G-D/1G-DMulti-mode Optical ModuleUACC-OM-MM-10G-D:Multi-mode, duplex, ber transceiver module.The 10 Gbps Multi-mode Optical Module is a duplex transceiver that delivers up to 10 Gbps speed over distancesup to 300 meters.UACC-OM-MM-1G-D:Multi-mode, duplex, ber transceiver module.The 1 Gbps Multi-mode Optical Module is a duplex transceiver that delivers up to 1.25 Gbps speed over distancesup to 550 meters.UACC-OM-MM-10G-DSupported Media Multi-Mode FiberConnector T ype(2) LCTX Wavelength Black Latch: 850 nmRX Wavelength Black Latch: 850 nmData Rate10 GbpsMax. Power Consumption0.8WCable Distance300 mOperating T emperature0 to 70° C (32 to 158° F)Pack Options2-pack, 20-packWARNING CLASS 1 LASER PRODUCT, IEC/EN 60825-1:2014 – Do not look into the ends of the ber optic cable or SFPmodule while converters are powered.UACC-OM-MM-1G-DSupported Media Multi-Mode FiberConnector T ype(2) LCTX Wavelength Black Latch: 850 nmRX Wavelength Black Latch: 850 nmData Rate 1.25 GbpsMax. Power Consumption0.66WCable Distance550 mOperating T emperature0 to 70° C (32 to 158° F)Pack Options2-pack, 20-packWARNING CLASS 1 LASER PRODUCT, IEC/EN 60825-1:2014 – Do not look into the ends of the ber optic cable or SFPmodule while converters are powered.Specifications are subject to change. Ubiquiti products are sold with a limited warranty described at: /support/warranty©2021 Ubiquiti Inc. All rights reserved. Ubiquiti, Ubiquiti Networks, the Ubiquiti U logo, the Ubiquiti beam logo, UniFi, and UniFi Network are trademarks or registered trademarks of Ubiquiti Inc. in theUnited States and in other countries. All other trademarks are the property of their respective owners.。

指令说‎明M‎a p In‎i tial‎i zati‎o n 地图‎初始化‎D estr‎u ctib‎l e Do‎o dad ‎- Des‎t ruct‎i ble ‎D ooda‎d Die‎s可破坏‎物体被摧毁‎Des‎t ruct‎i ble ‎D ooda‎d - W‎i thin‎Regi‎o n Di‎e s 在区‎域中被摧毁‎Dia‎l og -‎Dial‎o g Bu‎t ton ‎C lick‎按下对话‎按钮G‎a me -‎Time‎Of D‎a y 游戏‎中时间‎G ame ‎- Val‎u e Of‎Real‎Vari‎a ble ‎实数变量R‎e al数值‎Gam‎e - L‎o ad 读‎取Ga‎m e - ‎S ave ‎保存G‎a me -‎Hero‎Abil‎i ties‎Butt‎o n Cl‎i cked‎按下英雄‎升级技能按‎钮Ga‎m e - ‎B uild‎Stru‎c ture‎Butt‎o n Cl‎i cked‎按下建造‎按钮P‎l ayer‎- Ch‎a t Me‎s sage‎聊天信息‎Pla‎y er -‎Cine‎m atic‎Skip‎p ed 跳‎过电影‎P laye‎r - S‎e lect‎i on E‎v ent ‎选择事件‎Play‎e r - ‎K eybo‎a rd E‎v ent ‎键盘事件‎Play‎e r - ‎P rope‎r ties‎资源‎P laye‎r - A‎l lian‎c e Ch‎a nge(‎A ny) ‎同盟改变‎(任何) ‎Play‎e r - ‎A llia‎n ce C‎h ange‎(Spec‎i fic)‎同盟改变‎(指定)‎Pla‎y er -‎Vict‎o ry 胜‎利Pl‎a yer ‎- Def‎e at 失‎败Ti‎m e - ‎T ime ‎E laps‎e d 时间‎经过T‎i me -‎Peri‎o dic ‎E vent‎周期性事‎件Ti‎m e - ‎T imer‎Expi‎r es 计‎时器过期‎Unit‎- Sp‎e cifi‎c Uni‎t Eve‎n t 特定‎单位事件‎Unit‎- Pl‎a yer-‎O wned‎Unit‎Even‎t拥有单‎位事件‎U nit ‎- Gen‎e ric ‎U nit ‎E vent‎一般单位‎事件U‎n it -‎Unit‎Ente‎r s Re‎g ion ‎单位进入区‎域Un‎i t - ‎U nit ‎L eave‎s Reg‎i on 单‎位离开区域‎Uni‎t - U‎n it W‎i thin‎Rang‎e单位在‎范围中‎U nit ‎- Lif‎e生命‎Unit‎- Ma‎n a 法力‎Boo‎l ean ‎C ompa‎r ison‎布尔值B‎o olea‎n判断‎A bili‎t y Co‎m pari‎s on 技‎能判断‎D estr‎u ctib‎l e Co‎m pari‎s on 可‎破坏物体判‎断De‎s truc‎t ible‎-Type‎Comp‎a riso‎n可破坏‎物体类型判‎断Di‎a log ‎B utto‎n Com‎p aris‎o n 对话‎按钮判断‎Game‎Diff‎i cult‎y Com‎p aris‎o n 游戏‎难度判断‎Game‎Spee‎d Com‎p aris‎o n 游戏‎速度判断‎Hero‎Skil‎l Com‎p aris‎o n 英雄‎技能判断‎Inte‎g er C‎o mpar‎i son ‎整数Int‎e ger判‎断It‎e m Co‎m pari‎s on 物‎品判断‎I tem-‎C lass‎Comp‎a riso‎n物品种‎类判断‎I tem-‎T ype ‎C ompa‎r ison‎物品类型‎判断M‎e lee ‎A I Co‎m pari‎s on 多‎人对战AI‎判断O‎r der ‎C ompa‎r ison‎命令判断‎Pla‎y er C‎o mpar‎i son ‎玩家判断‎Play‎e r Co‎l or C‎o mpar‎i son ‎玩家颜色判‎断Pl‎a yer ‎C ontr‎o ller‎Comp‎a riso‎n玩家控‎制判断‎P laye‎r Slo‎t Sta‎t us C‎o mpar‎i son ‎玩家在线状‎态判断‎R ace ‎C ompa‎r ison‎种族判断‎Rea‎l Com‎p aris‎o n 实数‎R eal判‎断St‎r ing ‎C ompa‎r ison‎字符串S‎t ring‎判断T‎e ch-T‎y pe C‎o mpar‎i son ‎科技类型判‎断Tr‎i gger‎Comp‎a riso‎n触发器‎判断U‎n it C‎o mpar‎i son ‎单位判断‎Unit‎-Type‎Comp‎a riso‎n单位类‎型判断‎A nd 与‎Or ‎或An‎d, Mu‎l tipl‎e Con‎d itio‎n s 与，‎多个条件‎Or, ‎M ulti‎p le C‎o ndit‎i ons ‎或，多个条‎件Cr‎e ate ‎U nit ‎F acin‎g Ang‎l e 创建‎单位并指定‎面向角度‎创建单位，‎并指定其面‎向角度‎C reat‎e Uni‎t Fac‎i ng P‎o int ‎创建单位并‎指定面向点‎创建单位‎，并指定其‎面向点‎C reat‎e Cor‎p se 创‎建尸体创‎建单位的尸‎体Cr‎e ate ‎P erma‎n ent ‎C orps‎e创建永‎久的尸体‎创建永久存‎在的尸体‎Kill‎杀死杀‎死单位‎R emov‎e移除‎从游戏中移‎除单位‎E xplo‎d e 爆炸‎使单位以‎炸开形式死‎亡Re‎p lace‎替换用‎一个单位替‎换现有单位‎Hid‎e隐藏‎隐藏单位‎Unhi‎d e 解除‎隐藏解除‎隐藏单位‎Chan‎g e Co‎l or 改‎变颜色改‎变单位颜色‎，控制权不‎会改变‎C hang‎e Own‎e r 改变‎所有者改‎变单位的所‎有者S‎h ared‎Visi‎o n 分享‎视野玩家‎分享单位的‎视野M‎o ve U‎n it (‎I nsta‎n tly)‎移动单位‎(立即)‎让单位瞬‎间移动到另‎一位置‎M ove ‎U nit ‎A nd F‎a ce A‎n gle ‎(Inst‎a ntly‎)移动单‎位并指定面‎向角度 (‎立即) 让‎单位瞬间移‎动到另一位‎置，并指定‎面向角度‎Move‎Unit‎And ‎F ace ‎P oint‎(Ins‎t antl‎y) 搬移‎单位并指定‎面向点 (‎立即) 让‎单位瞬间移‎动到另一位‎置，并指定‎面向点‎S et L‎i fe(T‎o Per‎c enta‎g e) 设‎置生命 (‎百分比) ‎以百分比方‎式设置生命‎值Se‎t Man‎a(To ‎P erce‎n tage‎)设置法‎力 (百分‎比) 以百‎分比方式设‎置法力值‎Set ‎L ife(‎T o Va‎l ue) ‎设置生命‎(数值) ‎设置生命值‎Set‎Mana‎(To V‎a lue)‎设置法力‎(数值)‎设置法力‎值Ma‎k e In‎v ulne‎r able‎/Vuln‎e rabl‎e成为无‎敌的/可被‎攻击的设‎定单位为无‎敌的/可被‎攻击的状态‎Pau‎s e/Un‎p ause‎暂停/解‎除暂停暂‎停/解除暂‎停单位的动‎作，玩家将‎不可控制单‎位Pa‎u se/U‎n paus‎e All‎Unit‎暂停/解‎除暂停所有‎单位暂停‎/解除暂停‎所有单位的‎动作，玩家‎将不可控制‎单位P‎a use/‎U npau‎s e Ex‎p irat‎i on T‎i mer ‎暂停/解除‎暂停到期的‎定时器暂‎停/解除暂‎停到期的定‎时器A‎d d Ex‎p irat‎i on T‎i mer ‎增加到期的‎定时器增‎加到期的定‎时器M‎a ke U‎n it E‎x plod‎e On ‎D eath‎成为爆炸‎式死亡单位‎使单位死‎亡方式成为‎以炸开形式‎死亡S‎u spen‎d Cor‎p se D‎e cay ‎暂缓尸体腐‎烂让尸体‎腐烂暂缓‎Rese‎t Abi‎l ity ‎C oold‎o wns ‎重设技能冷‎却恢复技‎能冷却到默‎认值S‎e t Bu‎i ldin‎g Con‎s truc‎t ion ‎P rogr‎e ss 设‎置建造建筑‎物进度设‎置建造建筑‎物所要消耗‎的时间‎S et B‎u ildi‎n g Up‎g rade‎Prog‎r ess ‎设置建造升‎级进度设‎置建筑升级‎所要消耗的‎时间M‎a ke U‎n it S‎l eep ‎成为睡眠单‎位使单位‎处于睡眠状‎态Ma‎k e Un‎i t Sl‎e ep A‎t Nig‎h t 成为‎夜间睡眠单‎位使单位‎在夜晚的时‎候处于睡眠‎状态W‎a ke U‎p醒来‎使睡眠中的‎单位醒过来‎Tur‎n Ala‎r m Ge‎n erat‎i on O‎n/Off‎警戒范围‎开/关打‎开/关闭单‎位警戒范围‎Res‎c ue U‎n it 营‎救单位设‎置单位被营‎救Ma‎k e Re‎s cuab‎l e 成为‎可营救的‎设置单位为‎可营救单位‎，玩家接触‎时营救单位‎将加入玩家‎阵营S‎e t Re‎s cue ‎R ange‎设置营救‎范围设置‎进入范围后‎单位即被营‎救Se‎t Res‎c ue B‎e havi‎o r Fo‎r Uni‎t s 设置‎单位营救行‎为设置营‎救后单位颜‎色是否变化‎Set‎Resc‎u e Be‎h avio‎r For‎Buil‎d ings‎设置建筑‎营救行为‎设置营救后‎建筑颜色是‎否变化‎E nabl‎e/Dis‎a ble ‎S uppl‎y Usa‎g e 开启‎/关闭人口‎上限开启‎/关闭人口‎上限M‎a ke U‎n it F‎a ce U‎n it 使‎单位面向单‎位使单位‎面向单位‎Make‎Unit‎Face‎Poin‎t使单位‎面向地点‎使单位面向‎地点M‎a ke U‎n it F‎a ce A‎n gle ‎使单位面向‎角度使单‎位面向角度‎Set‎Move‎m ent ‎S peed‎设置移动‎速度设置‎移动单位速‎度Tu‎r n Co‎l lisi‎o n On‎/Off ‎碰撞开/关‎设置单位‎是否可与其‎他单位重叠‎Set‎Acqu‎i siti‎o n Ra‎n ge 设‎置获得范围‎设置单位‎的获得物品‎范围S‎e t Cu‎s tom ‎V alue‎设置自定‎义数值设‎置自定义数‎值Re‎m ove ‎B uffs‎移除持续‎性魔法移‎除单位上的‎持续性魔法‎Rem‎o ve B‎u ffs ‎B y Ty‎p e 移除‎持续性魔法‎类型按类‎型移除单位‎上的持续性‎魔法A‎d d Ab‎i lity‎增加技能‎增加单位‎的技能‎R emov‎e Abi‎l ity ‎移除技能‎移除单位的‎技能I‎s sue ‎O rder‎Targ‎e ting‎A Un‎i t 当前‎目标是一个‎单位的命令‎让单位执‎行目标是单‎位的命令‎Issu‎e Ord‎e r Ta‎r geti‎n g A ‎P oint‎当前目标‎是一个点的‎命令让单‎位执行目标‎是地点的命‎令Is‎s ue O‎r der ‎T arge‎t ing ‎A Des‎t ruct‎i ble ‎当前目标是‎一个可破坏‎物体的命令‎让单位执‎行目标是可‎破坏物体的‎命令I‎s sue ‎O rder‎With‎No T‎a rget‎没有目标‎的命令让‎单位执行没‎有目标的命‎令Is‎s ue T‎r ain/‎U pgra‎d e Or‎d er 训‎练/升级的‎命令执行‎训练/升级‎的命令‎I ssue‎Rese‎a rch ‎O rder‎研究科技‎的命令执‎行研究科技‎的命令‎I ssue‎Buil‎d Ord‎e r 建造‎的命令执‎行建造的命‎令‎‎。

目录第一部分 (3)第二部分 (12)Letter A (12)Letter B (14)Letter C (15)Letter D (17)Letter E (19)Letter F (20)Letter G (21)Letter H (22)Letter I (23)Letter K (24)Letter L (24)Letter M (26)Letter N (27)Letter O (29)Letter P (29)Letter R (31)Letter S (32)Letter T (35)Letter U (36)Letter W (37)Letter Z (37)第三部分 (37)A (37)B (38)C (38)D (40)E (40)F (41)G (41)H (42)L (42)J (43)L (43)M (43)N (44)O (44)P (44)Q (45)R (46)S (46)U (47)V (48)第一部分[ ] intensity 强度[ ] Regression 回归[ ] Loss function 损失函数[ ] non-convex 非凸函数[ ] neural network 神经网络[ ] supervised learning 监督学习[ ] regression problem 回归问题处理的是连续的问题[ ] classification problem 分类问题处理的问题是离散的而不是连续的回归问题和分类问题的区别应该在于回归问题的结果是连续的，分类问题的结果是离散的。

[ ]discreet value 离散值[ ] support vector machines 支持向量机,用来处理分类算法中输入的维度不单一的情况（甚至输入维度为无穷）[ ] learning theory 学习理论[ ] learning algorithms 学习算法[ ] unsupervised learning 无监督学习[ ] gradient descent 梯度下降[ ] linear regression 线性回归[ ] Neural Network 神经网络[ ] gradient descent 梯度下降监督学习的一种算法，用来拟合的算法[ ] normal equations[ ] linear algebra 线性代数原谅我英语不太好[ ] superscript上标[ ] exponentiation 指数[ ] training set 训练集合[ ] training example 训练样本[ ] hypothesis 假设，用来表示学习算法的输出，叫我们不要太纠结H的意思，因为这只是历史的惯例[ ] LMS algorithm “least mean squares” 最小二乘法算法[ ] batch gradient descent 批量梯度下降，因为每次都会计算最小拟合的方差，所以运算慢[ ] constantly gradient descent 字幕组翻译成“随机梯度下降” 我怎么觉得是“常量梯度下降”也就是梯度下降的运算次数不变，一般比批量梯度下降速度快，但是通常不是那么准确[ ] iterative algorithm 迭代算法[ ] partial derivative 偏导数[ ] contour 等高线[ ] quadratic function 二元函数[ ] locally weighted regression局部加权回归[ ] underfitting欠拟合[ ] overfitting 过拟合[ ] non-parametric learning algorithms 无参数学习算法[ ] parametric learning algorithm 参数学习算法[ ] other[ ] activation 激活值[ ] activation function 激活函数[ ] additive noise 加性噪声[ ] autoencoder 自编码器[ ] Autoencoders 自编码算法[ ] average firing rate 平均激活率[ ] average sum-of-squares error 均方差[ ] backpropagation 后向传播[ ] basis 基[ ] basis feature vectors 特征基向量[50 ] batch gradient ascent 批量梯度上升法[ ] Bayesian regularization method 贝叶斯规则化方法[ ] Bernoulli random variable 伯努利随机变量[ ] bias term 偏置项[ ] binary classfication 二元分类[ ] class labels 类型标记[ ] concatenation 级联[ ] conjugate gradient 共轭梯度[ ] contiguous groups 联通区域[ ] convex optimization software 凸优化软件[ ] convolution 卷积[ ] cost function 代价函数[ ] covariance matrix 协方差矩阵[ ] DC component 直流分量[ ] decorrelation 去相关[ ] degeneracy 退化[ ] demensionality reduction 降维[ ] derivative 导函数[ ] diagonal 对角线[ ] diffusion of gradients 梯度的弥散[ ] eigenvalue 特征值[ ] eigenvector 特征向量[ ] error term 残差[ ] feature matrix 特征矩阵[ ] feature standardization 特征标准化[ ] feedforward architectures 前馈结构算法[ ] feedforward neural network 前馈神经网络[ ] feedforward pass 前馈传导[ ] fine-tuned 微调[ ] first-order feature 一阶特征[ ] forward pass 前向传导[ ] forward propagation 前向传播[ ] Gaussian prior 高斯先验概率[ ] generative model 生成模型[ ] gradient descent 梯度下降[ ] Greedy layer-wise training 逐层贪婪训练方法[ ] grouping matrix 分组矩阵[ ] Hadamard product 阿达马乘积[ ] Hessian matrix Hessian 矩阵[ ] hidden layer 隐含层[ ] hidden units 隐藏神经元[ ] Hierarchical grouping 层次型分组[ ] higher-order features 更高阶特征[ ] highly non-convex optimization problem 高度非凸的优化问题[ ] histogram 直方图[ ] hyperbolic tangent 双曲正切函数[ ] hypothesis 估值，假设[ ] identity activation function 恒等激励函数[ ] IID 独立同分布[ ] illumination 照明[100 ] inactive 抑制[ ] independent component analysis 独立成份分析[ ] input domains 输入域[ ] input layer 输入层[ ] intensity 亮度/灰度[ ] intercept term 截距[ ] KL divergence 相对熵[ ] KL divergence KL分散度[ ] k-Means K-均值[ ] learning rate 学习速率[ ] least squares 最小二乘法[ ] linear correspondence 线性响应[ ] linear superposition 线性叠加[ ] line-search algorithm 线搜索算法[ ] local mean subtraction 局部均值消减[ ] local optima 局部最优解[ ] logistic regression 逻辑回归[ ] loss function 损失函数[ ] low-pass filtering 低通滤波[ ] magnitude 幅值[ ] MAP 极大后验估计[ ] maximum likelihood estimation 极大似然估计[ ] mean 平均值[ ] MFCC Mel 倒频系数[ ] multi-class classification 多元分类[ ] neural networks 神经网络[ ] neuron 神经元[ ] Newton’s method 牛顿法[ ] non-convex function 非凸函数[ ] non-linear feature 非线性特征[ ] norm 范式[ ] norm bounded 有界范数[ ] norm constrained 范数约束[ ] normalization 归一化[ ] numerical roundoff errors 数值舍入误差[ ] numerically checking 数值检验[ ] numerically reliable 数值计算上稳定[ ] object detection 物体检测[ ] objective function 目标函数[ ] off-by-one error 缺位错误[ ] orthogonalization 正交化[ ] output layer 输出层[ ] overall cost function 总体代价函数[ ] over-complete basis 超完备基[ ] over-fitting 过拟合[ ] parts of objects 目标的部件[ ] part-whole decompostion 部分-整体分解[ ] PCA 主元分析[ ] penalty term 惩罚因子[ ] per-example mean subtraction 逐样本均值消减[150 ] pooling 池化[ ] pretrain 预训练[ ] principal components analysis 主成份分析[ ] quadratic constraints 二次约束[ ] RBMs 受限Boltzman机[ ] reconstruction based models 基于重构的模型[ ] reconstruction cost 重建代价[ ] reconstruction term 重构项[ ] redundant 冗余[ ] reflection matrix 反射矩阵[ ] regularization 正则化[ ] regularization term 正则化项[ ] rescaling 缩放[ ] robust 鲁棒性[ ] run 行程[ ] second-order feature 二阶特征[ ] sigmoid activation function S型激励函数[ ] significant digits 有效数字[ ] singular value 奇异值[ ] singular vector 奇异向量[ ] smoothed L1 penalty 平滑的L1范数惩罚[ ] Smoothed topographic L1 sparsity penalty 平滑地形L1稀疏惩罚函数[ ] smoothing 平滑[ ] Softmax Regresson Softmax回归[ ] sorted in decreasing order 降序排列[ ] source features 源特征[ ] sparse autoencoder 消减归一化[ ] Sparsity 稀疏性[ ] sparsity parameter 稀疏性参数[ ] sparsity penalty 稀疏惩罚[ ] square function 平方函数[ ] squared-error 方差[ ] stationary 平稳性（不变性）[ ] stationary stochastic process 平稳随机过程[ ] step-size 步长值[ ] supervised learning 监督学习[ ] symmetric positive semi-definite matrix 对称半正定矩阵[ ] symmetry breaking 对称失效[ ] tanh function 双曲正切函数[ ] the average activation 平均活跃度[ ] the derivative checking method 梯度验证方法[ ] the empirical distribution 经验分布函数[ ] the energy function 能量函数[ ] the Lagrange dual 拉格朗日对偶函数[ ] the log likelihood 对数似然函数[ ] the pixel intensity value 像素灰度值[ ] the rate of convergence 收敛速度[ ] topographic cost term 拓扑代价项[ ] topographic ordered 拓扑秩序[ ] transformation 变换[200 ] translation invariant 平移不变性[ ] trivial answer 平凡解[ ] under-complete basis 不完备基[ ] unrolling 组合扩展[ ] unsupervised learning 无监督学习[ ] variance 方差[ ] vecotrized implementation 向量化实现[ ] vectorization 矢量化[ ] visual cortex 视觉皮层[ ] weight decay 权重衰减[ ] weighted average 加权平均值[ ] whitening 白化[ ] zero-mean 均值为零第二部分Letter A[ ] Accumulated error backpropagation 累积误差逆传播[ ] Activation Function 激活函数[ ] Adaptive Resonance Theory/ART 自适应谐振理论[ ] Addictive model 加性学习[ ] Adversarial Networks 对抗网络[ ] Affine Layer 仿射层[ ] Affinity matrix 亲和矩阵[ ] Agent 代理/ 智能体[ ] Algorithm 算法[ ] Alpha-beta pruning α-β剪枝[ ] Anomaly detection 异常检测[ ] Approximation 近似[ ] Area Under ROC Curve／AUC Roc 曲线下面积[ ] Artificial General Intelligence/AGI 通用人工智能[ ] Artificial Intelligence/AI 人工智能[ ] Association analysis 关联分析[ ] Attention mechanism 注意力机制[ ] Attribute conditional independence assumption 属性条件独立性假设[ ] Attribute space 属性空间[ ] Attribute value 属性值[ ] Autoencoder 自编码器[ ] Automatic speech recognition 自动语音识别[ ] Automatic summarization 自动摘要[ ] Average gradient 平均梯度[ ] Average-Pooling 平均池化Letter B[ ] Backpropagation Through Time 通过时间的反向传播[ ] Backpropagation/BP 反向传播[ ] Base learner 基学习器[ ] Base learning algorithm 基学习算法[ ] Batch Normalization/BN 批量归一化[ ] Bayes decision rule 贝叶斯判定准则[250 ] Bayes Model Averaging／BMA 贝叶斯模型平均[ ] Bayes optimal classifier 贝叶斯最优分类器[ ] Bayesian decision theory 贝叶斯决策论[ ] Bayesian network 贝叶斯网络[ ] Between-class scatter matrix 类间散度矩阵[ ] Bias 偏置/ 偏差[ ] Bias-variance decomposition 偏差-方差分解[ ] Bias-Variance Dilemma 偏差–方差困境[ ] Bi-directional Long-Short Term Memory/Bi-LSTM 双向长短期记忆[ ] Binary classification 二分类[ ] Binomial test 二项检验[ ] Bi-partition 二分法[ ] Boltzmann machine 玻尔兹曼机[ ] Bootstrap sampling 自助采样法／可重复采样／有放回采样[ ] Bootstrapping 自助法[ ] Break-Event Point／BEP 平衡点Letter C[ ] Calibration 校准[ ] Cascade-Correlation 级联相关[ ] Categorical attribute 离散属性[ ] Class-conditional probability 类条件概率[ ] Classification and regression tree/CART 分类与回归树[ ] Classifier 分类器[ ] Class-imbalance 类别不平衡[ ] Closed -form 闭式[ ] Cluster 簇/类/集群[ ] Cluster analysis 聚类分析[ ] Clustering 聚类[ ] Clustering ensemble 聚类集成[ ] Co-adapting 共适应[ ] Coding matrix 编码矩阵[ ] COLT 国际学习理论会议[ ] Committee-based learning 基于委员会的学习[ ] Competitive learning 竞争型学习[ ] Component learner 组件学习器[ ] Comprehensibility 可解释性[ ] Computation Cost 计算成本[ ] Computational Linguistics 计算语言学[ ] Computer vision 计算机视觉[ ] Concept drift 概念漂移[ ] Concept Learning System /CLS 概念学习系统[ ] Conditional entropy 条件熵[ ] Conditional mutual information 条件互信息[ ] Conditional Probability Table／CPT 条件概率表[ ] Conditional random field/CRF 条件随机场[ ] Conditional risk 条件风险[ ] Confidence 置信度[ ] Confusion matrix 混淆矩阵[300 ] Connection weight 连接权[ ] Connectionism 连结主义[ ] Consistency 一致性／相合性[ ] Contingency table 列联表[ ] Continuous attribute 连续属性[ ] Convergence 收敛[ ] Conversational agent 会话智能体[ ] Convex quadratic programming 凸二次规划[ ] Convexity 凸性[ ] Convolutional neural network/CNN 卷积神经网络[ ] Co-occurrence 同现[ ] Correlation coefficient 相关系数[ ] Cosine similarity 余弦相似度[ ] Cost curve 成本曲线[ ] Cost Function 成本函数[ ] Cost matrix 成本矩阵[ ] Cost-sensitive 成本敏感[ ] Cross entropy 交叉熵[ ] Cross validation 交叉验证[ ] Crowdsourcing 众包[ ] Curse of dimensionality 维数灾难[ ] Cut point 截断点[ ] Cutting plane algorithm 割平面法Letter D[ ] Data mining 数据挖掘[ ] Data set 数据集[ ] Decision Boundary 决策边界[ ] Decision stump 决策树桩[ ] Decision tree 决策树／判定树[ ] Deduction 演绎[ ] Deep Belief Network 深度信念网络[ ] Deep Convolutional Generative Adversarial Network/DCGAN 深度卷积生成对抗网络[ ] Deep learning 深度学习[ ] Deep neural network/DNN 深度神经网络[ ] Deep Q-Learning 深度Q 学习[ ] Deep Q-Network 深度Q 网络[ ] Density estimation 密度估计[ ] Density-based clustering 密度聚类[ ] Differentiable neural computer 可微分神经计算机[ ] Dimensionality reduction algorithm 降维算法[ ] Directed edge 有向边[ ] Disagreement measure 不合度量[ ] Discriminative model 判别模型[ ] Discriminator 判别器[ ] Distance measure 距离度量[ ] Distance metric learning 距离度量学习[ ] Distribution 分布[ ] Divergence 散度[350 ] Diversity measure 多样性度量／差异性度量[ ] Domain adaption 领域自适应[ ] Downsampling 下采样[ ] D-separation （Directed separation）有向分离[ ] Dual problem 对偶问题[ ] Dummy node 哑结点[ ] Dynamic Fusion 动态融合[ ] Dynamic programming 动态规划Letter E[ ] Eigenvalue decomposition 特征值分解[ ] Embedding 嵌入[ ] Emotional analysis 情绪分析[ ] Empirical conditional entropy 经验条件熵[ ] Empirical entropy 经验熵[ ] Empirical error 经验误差[ ] Empirical risk 经验风险[ ] End-to-End 端到端[ ] Energy-based model 基于能量的模型[ ] Ensemble learning 集成学习[ ] Ensemble pruning 集成修剪[ ] Error Correcting Output Codes／ECOC 纠错输出码[ ] Error rate 错误率[ ] Error-ambiguity decomposition 误差-分歧分解[ ] Euclidean distance 欧氏距离[ ] Evolutionary computation 演化计算[ ] Expectation-Maximization 期望最大化[ ] Expected loss 期望损失[ ] Exploding Gradient Problem 梯度爆炸问题[ ] Exponential loss function 指数损失函数[ ] Extreme Learning Machine/ELM 超限学习机Letter F[ ] Factorization 因子分解[ ] False negative 假负类[ ] False positive 假正类[ ] False Positive Rate/FPR 假正例率[ ] Feature engineering 特征工程[ ] Feature selection 特征选择[ ] Feature vector 特征向量[ ] Featured Learning 特征学习[ ] Feedforward Neural Networks/FNN 前馈神经网络[ ] Fine-tuning 微调[ ] Flipping output 翻转法[ ] Fluctuation 震荡[ ] Forward stagewise algorithm 前向分步算法[ ] Frequentist 频率主义学派[ ] Full-rank matrix 满秩矩阵[400 ] Functional neuron 功能神经元Letter G[ ] Gain ratio 增益率[ ] Game theory 博弈论[ ] Gaussian kernel function 高斯核函数[ ] Gaussian Mixture Model 高斯混合模型[ ] General Problem Solving 通用问题求解[ ] Generalization 泛化[ ] Generalization error 泛化误差[ ] Generalization error bound 泛化误差上界[ ] Generalized Lagrange function 广义拉格朗日函数[ ] Generalized linear model 广义线性模型[ ] Generalized Rayleigh quotient 广义瑞利商[ ] Generative Adversarial Networks/GAN 生成对抗网络[ ] Generative Model 生成模型[ ] Generator 生成器[ ] Genetic Algorithm/GA 遗传算法[ ] Gibbs sampling 吉布斯采样[ ] Gini index 基尼指数[ ] Global minimum 全局最小[ ] Global Optimization 全局优化[ ] Gradient boosting 梯度提升[ ] Gradient Descent 梯度下降[ ] Graph theory 图论[ ] Ground-truth 真相／真实Letter H[ ] Hard margin 硬间隔[ ] Hard voting 硬投票[ ] Harmonic mean 调和平均[ ] Hesse matrix 海塞矩阵[ ] Hidden dynamic model 隐动态模型[ ] Hidden layer 隐藏层[ ] Hidden Markov Model/HMM 隐马尔可夫模型[ ] Hierarchical clustering 层次聚类[ ] Hilbert space 希尔伯特空间[ ] Hinge loss function 合页损失函数[ ] Hold-out 留出法[ ] Homogeneous 同质[ ] Hybrid computing 混合计算[ ] Hyperparameter 超参数[ ] Hypothesis 假设[ ] Hypothesis test 假设验证Letter I[ ] ICML 国际机器学习会议[450 ] Improved iterative scaling/IIS 改进的迭代尺度法[ ] Incremental learning 增量学习[ ] Independent and identically distributed/i.i.d. 独立同分布[ ] Independent Component Analysis/ICA 独立成分分析[ ] Indicator function 指示函数[ ] Individual learner 个体学习器[ ] Induction 归纳[ ] Inductive bias 归纳偏好[ ] Inductive learning 归纳学习[ ] Inductive Logic Programming／ILP 归纳逻辑程序设计[ ] Information entropy 信息熵[ ] Information gain 信息增益[ ] Input layer 输入层[ ] Insensitive loss 不敏感损失[ ] Inter-cluster similarity 簇间相似度[ ] International Conference for Machine Learning/ICML 国际机器学习大会[ ] Intra-cluster similarity 簇内相似度[ ] Intrinsic value 固有值[ ] Isometric Mapping/Isomap 等度量映射[ ] Isotonic regression 等分回归[ ] Iterative Dichotomiser 迭代二分器Letter K[ ] Kernel method 核方法[ ] Kernel trick 核技巧[ ] Kernelized Linear Discriminant Analysis／KLDA 核线性判别分析[ ] K-fold cross validation k 折交叉验证／k 倍交叉验证[ ] K-Means Clustering K –均值聚类[ ] K-Nearest Neighbours Algorithm/KNN K近邻算法[ ] Knowledge base 知识库[ ] Knowledge Representation 知识表征Letter L[ ] Label space 标记空间[ ] Lagrange duality 拉格朗日对偶性[ ] Lagrange multiplier 拉格朗日乘子[ ] Laplace smoothing 拉普拉斯平滑[ ] Laplacian correction 拉普拉斯修正[ ] Latent Dirichlet Allocation 隐狄利克雷分布[ ] Latent semantic analysis 潜在语义分析[ ] Latent variable 隐变量[ ] Lazy learning 懒惰学习[ ] Learner 学习器[ ] Learning by analogy 类比学习[ ] Learning rate 学习率[ ] Learning Vector Quantization/LVQ 学习向量量化[ ] Least squares regression tree 最小二乘回归树[ ] Leave-One-Out/LOO 留一法[500 ] linear chain conditional random field 线性链条件随机场[ ] Linear Discriminant Analysis／LDA 线性判别分析[ ] Linear model 线性模型[ ] Linear Regression 线性回归[ ] Link function 联系函数[ ] Local Markov property 局部马尔可夫性[ ] Local minimum 局部最小[ ] Log likelihood 对数似然[ ] Log odds／logit 对数几率[ ] Logistic Regression Logistic 回归[ ] Log-likelihood 对数似然[ ] Log-linear regression 对数线性回归[ ] Long-Short Term Memory/LSTM 长短期记忆[ ] Loss function 损失函数Letter M[ ] Machine translation/MT 机器翻译[ ] Macron-P 宏查准率[ ] Macron-R 宏查全率[ ] Majority voting 绝对多数投票法[ ] Manifold assumption 流形假设[ ] Manifold learning 流形学习[ ] Margin theory 间隔理论[ ] Marginal distribution 边际分布[ ] Marginal independence 边际独立性[ ] Marginalization 边际化[ ] Markov Chain Monte Carlo/MCMC 马尔可夫链蒙特卡罗方法[ ] Markov Random Field 马尔可夫随机场[ ] Maximal clique 最大团[ ] Maximum Likelihood Estimation/MLE 极大似然估计／极大似然法[ ] Maximum margin 最大间隔[ ] Maximum weighted spanning tree 最大带权生成树[ ] Max-Pooling 最大池化[ ] Mean squared error 均方误差[ ] Meta-learner 元学习器[ ] Metric learning 度量学习[ ] Micro-P 微查准率[ ] Micro-R 微查全率[ ] Minimal Description Length/MDL 最小描述长度[ ] Minimax game 极小极大博弈[ ] Misclassification cost 误分类成本[ ] Mixture of experts 混合专家[ ] Momentum 动量[ ] Moral graph 道德图／端正图[ ] Multi-class classification 多分类[ ] Multi-document summarization 多文档摘要[ ] Multi-layer feedforward neural networks 多层前馈神经网络[ ] Multilayer Perceptron/MLP 多层感知器[ ] Multimodal learning 多模态学习[550 ] Multiple Dimensional Scaling 多维缩放[ ] Multiple linear regression 多元线性回归[ ] Multi-response Linear Regression ／MLR 多响应线性回归[ ] Mutual information 互信息Letter N[ ] Naive bayes 朴素贝叶斯[ ] Naive Bayes Classifier 朴素贝叶斯分类器[ ] Named entity recognition 命名实体识别[ ] Nash equilibrium 纳什均衡[ ] Natural language generation/NLG 自然语言生成[ ] Natural language processing 自然语言处理[ ] Negative class 负类[ ] Negative correlation 负相关法[ ] Negative Log Likelihood 负对数似然[ ] Neighbourhood Component Analysis/NCA 近邻成分分析[ ] Neural Machine Translation 神经机器翻译[ ] Neural Turing Machine 神经图灵机[ ] Newton method 牛顿法[ ] NIPS 国际神经信息处理系统会议[ ] No Free Lunch Theorem／NFL 没有免费的午餐定理[ ] Noise-contrastive estimation 噪音对比估计[ ] Nominal attribute 列名属性[ ] Non-convex optimization 非凸优化[ ] Nonlinear model 非线性模型[ ] Non-metric distance 非度量距离[ ] Non-negative matrix factorization 非负矩阵分解[ ] Non-ordinal attribute 无序属性[ ] Non-Saturating Game 非饱和博弈[ ] Norm 范数[ ] Normalization 归一化[ ] Nuclear norm 核范数[ ] Numerical attribute 数值属性Letter O[ ] Objective function 目标函数[ ] Oblique decision tree 斜决策树[ ] Occam’s razor 奥卡姆剃刀[ ] Odds 几率[ ] Off-Policy 离策略[ ] One shot learning 一次性学习[ ] One-Dependent Estimator／ODE 独依赖估计[ ] On-Policy 在策略[ ] Ordinal attribute 有序属性[ ] Out-of-bag estimate 包外估计[ ] Output layer 输出层[ ] Output smearing 输出调制法[ ] Overfitting 过拟合／过配[600 ] Oversampling 过采样Letter P[ ] Paired t-test 成对t 检验[ ] Pairwise 成对型[ ] Pairwise Markov property 成对马尔可夫性[ ] Parameter 参数[ ] Parameter estimation 参数估计[ ] Parameter tuning 调参[ ] Parse tree 解析树[ ] Particle Swarm Optimization/PSO 粒子群优化算法[ ] Part-of-speech tagging 词性标注[ ] Perceptron 感知机[ ] Performance measure 性能度量[ ] Plug and Play Generative Network 即插即用生成网络[ ] Plurality voting 相对多数投票法[ ] Polarity detection 极性检测[ ] Polynomial kernel function 多项式核函数[ ] Pooling 池化[ ] Positive class 正类[ ] Positive definite matrix 正定矩阵[ ] Post-hoc test 后续检验[ ] Post-pruning 后剪枝[ ] potential function 势函数[ ] Precision 查准率／准确率[ ] Prepruning 预剪枝[ ] Principal component analysis/PCA 主成分分析[ ] Principle of multiple explanations 多释原则[ ] Prior 先验[ ] Probability Graphical Model 概率图模型[ ] Proximal Gradient Descent/PGD 近端梯度下降[ ] Pruning 剪枝[ ] Pseudo-label 伪标记[ ] Letter Q[ ] Quantized Neural Network 量子化神经网络[ ] Quantum computer 量子计算机[ ] Quantum Computing 量子计算[ ] Quasi Newton method 拟牛顿法Letter R[ ] Radial Basis Function／RBF 径向基函数[ ] Random Forest Algorithm 随机森林算法[ ] Random walk 随机漫步[ ] Recall 查全率／召回率[ ] Receiver Operating Characteristic/ROC 受试者工作特征[ ] Rectified Linear Unit/ReLU 线性修正单元[650 ] Recurrent Neural Network 循环神经网络[ ] Recursive neural network 递归神经网络[ ] Reference model 参考模型[ ] Regression 回归[ ] Regularization 正则化[ ] Reinforcement learning/RL 强化学习[ ] Representation learning 表征学习[ ] Representer theorem 表示定理[ ] reproducing kernel Hilbert space/RKHS 再生核希尔伯特空间[ ] Re-sampling 重采样法[ ] Rescaling 再缩放[ ] Residual Mapping 残差映射[ ] Residual Network 残差网络[ ] Restricted Boltzmann Machine/RBM 受限玻尔兹曼机[ ] Restricted Isometry Property/RIP 限定等距性[ ] Re-weighting 重赋权法[ ] Robustness 稳健性/鲁棒性[ ] Root node 根结点[ ] Rule Engine 规则引擎[ ] Rule learning 规则学习Letter S[ ] Saddle point 鞍点[ ] Sample space 样本空间[ ] Sampling 采样[ ] Score function 评分函数[ ] Self-Driving 自动驾驶[ ] Self-Organizing Map／SOM 自组织映射[ ] Semi-naive Bayes classifiers 半朴素贝叶斯分类器[ ] Semi-Supervised Learning 半监督学习[ ] semi-Supervised Support Vector Machine 半监督支持向量机[ ] Sentiment analysis 情感分析[ ] Separating hyperplane 分离超平面[ ] Sigmoid function Sigmoid 函数[ ] Similarity measure 相似度度量[ ] Simulated annealing 模拟退火[ ] Simultaneous localization and mapping 同步定位与地图构建[ ] Singular Value Decomposition 奇异值分解[ ] Slack variables 松弛变量[ ] Smoothing 平滑[ ] Soft margin 软间隔[ ] Soft margin maximization 软间隔最大化[ ] Soft voting 软投票[ ] Sparse representation 稀疏表征[ ] Sparsity 稀疏性[ ] Specialization 特化[ ] Spectral Clustering 谱聚类[ ] Speech Recognition 语音识别[ ] Splitting variable 切分变量[700 ] Squashing function 挤压函数[ ] Stability-plasticity dilemma 可塑性-稳定性困境[ ] Statistical learning 统计学习[ ] Status feature function 状态特征函[ ] Stochastic gradient descent 随机梯度下降[ ] Stratified sampling 分层采样[ ] Structural risk 结构风险[ ] Structural risk minimization/SRM 结构风险最小化[ ] Subspace 子空间[ ] Supervised learning 监督学习／有导师学习[ ] support vector expansion 支持向量展式[ ] Support Vector Machine/SVM 支持向量机[ ] Surrogat loss 替代损失[ ] Surrogate function 替代函数[ ] Symbolic learning 符号学习[ ] Symbolism 符号主义[ ] Synset 同义词集Letter T[ ] T-Distribution Stochastic Neighbour Embedding/t-SNE T –分布随机近邻嵌入[ ] Tensor 张量[ ] Tensor Processing Units/TPU 张量处理单元[ ] The least square method 最小二乘法[ ] Threshold 阈值[ ] Threshold logic unit 阈值逻辑单元[ ] Threshold-moving 阈值移动[ ] Time Step 时间步骤[ ] Tokenization 标记化[ ] Training error 训练误差[ ] Training instance 训练示例／训练例[ ] Transductive learning 直推学习[ ] Transfer learning 迁移学习[ ] Treebank 树库[ ] Tria-by-error 试错法[ ] True negative 真负类[ ] True positive 真正类[ ] True Positive Rate/TPR 真正例率[ ] Turing Machine 图灵机[ ] Twice-learning 二次学习Letter U[ ] Underfitting 欠拟合／欠配[ ] Undersampling 欠采样[ ] Understandability 可理解性[ ] Unequal cost 非均等代价[ ] Unit-step function 单位阶跃函数[ ] Univariate decision tree 单变量决策树[ ] Unsupervised learning 无监督学习／无导师学习[ ] Unsupervised layer-wise training 无监督逐层训练[ ] Upsampling 上采样Letter V[ ] Vanishing Gradient Problem 梯度消失问题[ ] Variational inference 变分推断[ ] VC Theory VC维理论[ ] Version space 版本空间[ ] Viterbi algorithm 维特比算法[760 ] Von Neumann architecture 冯· 诺伊曼架构Letter W[ ] Wasserstein GAN/WGAN Wasserstein生成对抗网络[ ] Weak learner 弱学习器[ ] Weight 权重[ ] Weight sharing 权共享[ ] Weighted voting 加权投票法[ ] Within-class scatter matrix 类内散度矩阵[ ] Word embedding 词嵌入[ ] Word sense disambiguation 词义消歧Letter Z[ ] Zero-data learning 零数据学习[ ] Zero-shot learning 零次学习第三部分A[ ] approximations近似值[ ] arbitrary随意的[ ] affine仿射的[ ] arbitrary任意的[ ] amino acid氨基酸[ ] amenable经得起检验的[ ] axiom公理，原则[ ] abstract提取[ ] architecture架构，体系结构；建造业[ ] absolute绝对的[ ] arsenal军火库[ ] assignment分配[ ] algebra线性代数[ ] asymptotically无症状的[ ] appropriate恰当的B[ ] bias偏差[ ] brevity简短，简洁；短暂[800 ] broader广泛[ ] briefly简短的[ ] batch批量C[ ] convergence 收敛，集中到一点[ ] convex凸的[ ] contours轮廓[ ] constraint约束[ ] constant常理[ ] commercial商务的[ ] complementarity补充[ ] coordinate ascent同等级上升[ ] clipping剪下物；剪报；修剪[ ] component分量；部件[ ] continuous连续的[ ] covariance协方差[ ] canonical正规的，正则的[ ] concave非凸的[ ] corresponds相符合；相当；通信[ ] corollary推论[ ] concrete具体的事物，实在的东西[ ] cross validation交叉验证[ ] correlation相互关系[ ] convention约定[ ] cluster一簇[ ] centroids 质心，形心[ ] converge收敛[ ] computationally计算(机)的[ ] calculus计算D[ ] derive获得，取得[ ] dual二元的[ ] duality二元性；二象性；对偶性[ ] derivation求导；得到；起源[ ] denote预示，表示，是…的标志；意味着，[逻]指称[ ] divergence 散度；发散性[ ] dimension尺度，规格；维数[ ] dot小圆点[ ] distortion变形[ ] density概率密度函数[ ] discrete离散的[ ] discriminative有识别能力的[ ] diagonal对角[ ] dispersion分散，散开[ ] determinant决定因素[849 ] disjoint不相交的E[ ] encounter遇到[ ] ellipses椭圆[ ] equality等式[ ] extra额外的[ ] empirical经验；观察[ ] ennmerate例举，计数[ ] exceed超过，越出[ ] expectation期望[ ] efficient生效的[ ] endow赋予[ ] explicitly清楚的[ ] exponential family指数家族[ ] equivalently等价的F[ ] feasible可行的[ ] forary初次尝试[ ] finite有限的，限定的[ ] forgo摒弃，放弃[ ] fliter过滤[ ] frequentist最常发生的[ ] forward search前向式搜索[ ] formalize使定形G[ ] generalized归纳的[ ] generalization概括，归纳；普遍化；判断（根据不足）[ ] guarantee保证；抵押品[ ] generate形成，产生[ ] geometric margins几何边界[ ] gap裂口[ ] generative生产的；有生产力的H[ ] heuristic启发式的；启发法；启发程序[ ] hone怀恋；磨[ ] hyperplane超平面L[ ] initial最初的[ ] implement执行[ ] intuitive凭直觉获知的[ ] incremental增加的[900 ] intercept截距[ ] intuitious直觉[ ] instantiation例子[ ] indicator指示物，指示器[ ] interative重复的，迭代的[ ] integral积分[ ] identical相等的；完全相同的[ ] indicate表示，指出[ ] invariance不变性，恒定性[ ] impose把…强加于[ ] intermediate中间的[ ] interpretation解释，翻译J[ ] joint distribution联合概率L[ ] lieu替代[ ] logarithmic对数的，用对数表示的[ ] latent潜在的[ ] Leave-one-out cross validation留一法交叉验证M[ ] magnitude巨大[ ] mapping绘图，制图；映射[ ] matrix矩阵[ ] mutual相互的，共同的[ ] monotonically单调的[ ] minor较小的，次要的[ ] multinomial多项的[ ] multi-class classification二分类问题N[ ] nasty讨厌的[ ] notation标志，注释[ ] naïve朴素的O[ ] obtain得到[ ] oscillate摆动[ ] optimization problem最优化问题[ ] objective function目标函数[ ] optimal最理想的[ ] orthogonal(矢量，矩阵等)正交的[ ] orientation方向[ ] ordinary普通的[ ] occasionally偶然的P[ ] partial derivative偏导数[ ] property性质[ ] proportional成比例的[ ] primal原始的，最初的[ ] permit允许[ ] pseudocode伪代码[ ] permissible可允许的[ ] polynomial多项式[ ] preliminary预备[ ] precision精度[ ] perturbation 不安，扰乱[ ] poist假定，设想[ ] positive semi-definite半正定的[ ] parentheses圆括号[ ] posterior probability后验概率[ ] plementarity补充[ ] pictorially图像的[ ] parameterize确定…的参数[ ] poisson distribution柏松分布[ ] pertinent相关的Q[ ] quadratic二次的[ ] quantity量，数量；分量[ ] query疑问的R[ ] regularization使系统化；调整[ ] reoptimize重新优化[ ] restrict限制；限定；约束[ ] reminiscent回忆往事的；提醒的；使人联想…的（of）[ ] remark注意[ ] random variable随机变量[ ] respect考虑[ ] respectively各自的；分别的[ ] redundant过多的；冗余的S[ ] susceptible敏感的[ ] stochastic可能的；随机的[ ] symmetric对称的[ ] sophisticated复杂的[ ] spurious假的；伪造的[ ] subtract减去；减法器[ ] simultaneously同时发生地；同步地[ ] suffice满足[ ] scarce稀有的，难得的[ ] split分解，分离[ ] subset子集[ ] statistic统计量[ ] successive iteratious连续的迭代[ ] scale标度[ ] sort of有几分的[ ] squares平方T[ ] trajectory轨迹[ ] temporarily暂时的[ ] terminology专用名词[ ] tolerance容忍；公差[ ] thumb翻阅[ ] threshold阈，临界[ ] theorem定理[ ] tangent正弦U[ ] unit-length vector单位向量V[ ] valid有效的，正确的[ ] variance方差[ ] variable变量；变元[ ] vocabulary词汇[ ] valued经估价的；宝贵的[ ] W [1038 ] wrapper包装。

铁路专业词汇铁路专业词汇铁路；铁道railway railroad铁路线railway line；railroad line铁路网railway network；railroad network铁道科学railway science铁路技术railway technology铁路等级railway classification国有铁路national railway；state railway地方铁路local railway；regional railway私有铁路private railway合资铁路joint investment railway；jointly owned railway标准轨铁路standard-gage railway窄轨铁路narrow-gage railway米轨铁路meter-gage railway宽轨铁路broad-gage railway单线铁路single track railway双线铁路double track railway多线铁路multiple track railway重载铁路heavy haul railway高速铁路high speed railway电气化铁路；电力铁路electrified railway；electric railway干线铁路main line railway；trunk railway市郊铁路suburban railway地下铁道；地铁subway；metro；underground railway工业企业铁路industry railway矿山铁路mine railway轻轨铁路light railway；light rail高架铁路elevated railway单轨铁路；独轨铁路monorail；monorail railway磁浮铁路magnetic levitation railway；maglev森林铁路forest railway山区铁路mountain railway既有铁路existing railway新建铁路newly-built railway改建铁路reconstructed railway运营铁路railway in operation；operation；operating railway专用铁路special purpose railway干线trunk line；main line支线branch line铁路专用线railway special line货运专线railway line for freight traffic；freight special line；freight traffic only line 客运专线railway line for passenger traffic；passenger special line；passenger traffic onlyline客货运混合铁路railway line for mixed passenger and freight traffic铁路运营长度；运营里程operation length of railway；operating distance；revenue length 列车运行图train diagram铁路建筑长度construction length of railway区间section区段district轨距rail gage；rail gauge轮重wheel load轴重axle load最大轴重maximum allowable axle load限制轴重axle load limited限界clearance；gauge限界图clearance diagram铁路建筑限界railway construction clearance；structure clearance for railway；railway struction gauge基本建筑限界fundamental construction clearance；fundamental structure gauge桥梁建筑限界bridge construction clearance；bridge structure gauge隧道建筑界限tunnel construction clearance；tunnel structure gauge铁路机车车辆限界rolling stock clearance for railway；vehicle gauge机车车辆上部限界clearance limit for upper part of rolling stock机车车辆下部限界clearance limit for lower part of rolling stock装载限界loading clearance limit；loading gauge阔大货物限界clearance limit for freight with exceptional dimension；clearance limit for oversize commodities接触网限界clearance limt for overhead contract wire；clearance limit for overhead catenary system；overhead catenary system gauge列车与线路相互作用track-train interaction轮轨关系wheel-rail relation；wheel-rail interaction粘着系数adhesion coefficient车轮滑行wheel sliding；wheel skid车轮空转wheel slipping牵引种类kinds of traction；category of traction牵引方式mode of traction牵引定数tonnage rating；tonnage of traction装载系数loading coefficient速度speed持续速度continuous speed限制速度limited speed；speed restriction均衡速度balancing speed构造速度construction speed；design speed最高速度maximum speed临界速度critical speed重载列车heavy haul train高速列车high speed train超长超重列车exceptionally long and heavy train列车正面冲突train collision列车尾追train tail collision列车尾部防护train rear end protection伸缩运动fore and aft motion蛇行运动hunting；nosing列车压缩train running in列车拉伸train running out列车分离train separation列车颠覆train overturning列车动力学train dynamics列车空气动力学train acrodynamics机车车辆振动vibration of rolling stock纵向振动longitudinal vibration横向振动lateral vibration垂向振动vertical vibration摆滚振动rock-roll vibration浮沉振动bouncing；vibration测滚振动rolling ；vibration测摆振动swaying；vibration点头振动pitching；nodding摇头振动yawing；hunting机车车辆共振resonance of rolling stock机车车辆冲击impact of rolling纵向冲击longitudinal impact横向冲击lateral impact垂向冲击vertical impact货运站综合作业自动化automation of synthetic operations at freight station行车指挥自动化automation of traffic control编组场综合作业自动化automation of synthetic operations in marshalling yard铁路运营信息系统railway operation information system铁路数据交换系统railway data exchange system运营系统模拟simulation of operation system铁路法railway law铁道法规railway act铁路条例railway code铁路技术管理规程regulations of railway technical operation综合运输comprehensive transport；multi-mode transport；intermode transport国际铁路联运international railway through traffic大陆桥；洲际铁路transcontinental railway；intercontinental railway；land-railway 国际联运协定agreement of international through traffic国际联运议定书protocol of international through traffic国际铁路联运公约convention of international railway through traffic铁路新线建设newly-built railway construction铁路技术改造technical reform of railway；technical renovation of railway；betterment and improvement of railway铁路主要技术条件main technical standard of railway；main techincal requirement of railway单位工程unit project分部工程part project分项工程item project预可行性研究pre-feasibility study项目建议书proposed task of project可行性研究feasibility study设计阶段design phase；design stage三阶段设计three-step design；three-phase design两阶段设计two-step design；two-phase design一阶段设计one-step design；one-phase design初步设计preliminary design技术设计technical design扩大初步设计enlarged preliminary design；expanded preliminary design施工图设计construction detail design；working-drawing design变更设计altered design设计概算apporximate estimate of design；budgetary estimate of design个别概算individual approximate estimate综合概算comprehensive approximate estimate总概算sum of approximate estimate；total estimate；summary estimate修正总概算amended sum of approximate estimate；revised general estimate调整总概算adjusted sum of approximate estimate投资检算checking of investment预算定额rating of budget；rating form for budget概算定额rating of approximate estimate；rating form for estimate投资估算investment estimate估算指标index of estimate机械台班定额rating per machine per team；rating per machine-team工程直接费direct expense of project；direct cost of project工程间接费indirect expense of project；indirect cost of project工程预备费reserve fund of project设计鉴定certification of design；appraisal of design竣工决算final accounts of completed project铁路用地right-of-way铁路勘测railway reconnaissance调查测绘survey and drawing of investigation；investigation survey；investigation surveying and sketching地形调查topographic survey地貌调查topographic feature survey；geomorphologic survey地质调查geologic survey经济调查economic investigation；economic survey水文地质调查hydrogeologic survey土石成分调查survey of soil and rock composition土石物理力学性质physical and mechanical properties of soil and rock土石分类classificaion of soil and rock地基承载力bearing capacity of foundation；bearing capacity of ground；bearing of subgrade隧道围岩分级classification of tunnel surrounding rock地质图测绘survey and drawing of geological map；surveying and sketching of geological map勘探exploration；prospecting挖探excavation prospecting钻探boring；exploration drilling物探geophysical prospecting室内测试indoor test；laboratory test原位测试in situ test静力触探static sounding；static probing；cone penetration test动力触探试验dynamic penetration test标准贯入试验standard penetration test区域地质regional geology工程地质engineering geology不良地质unfavorable geology特殊地质special geology工程地质条件engineering geologic；requirement；engineering geologic condition气象资料meteorological data冻结深度freezing depth地震基本烈度basic intensity of earthquake；seismic basic intensity工程地质图engineering geological map地层柱状图column diagram of stratum；graphic logs of strata；drill log of stratum洪水调查flood survey河道调查river course survey冰凌调查ice floe survey；frazil ice survey汇水区流域特征调查survey of catchment basin characteristics水文断面hydrologic sectional drawing；dydrologic section；hydrologic cross-section 主河槽main river channel设计流速design current velocity设计高程；设计标高design elevation河流比降slope of river；comparable horizon of river历史洪水位historic flood level最高水位highest water level；HWL通航水位navigation water level；NWL桥涵水文hydrology of bridge and culvert水利半径hydraulic radius桥前壅水高度backwater height in front of bridge；top water level in front of bridge桥渡勘测设计survey and design of bridge crossing水面坡度slope of water surface水文测量hydrological survey泥石流流域catchment basin of debris flow分水岭watershed；dividing ridge汇水面积catchment area；water collecting area；drainage area洪水频率flood frequency设计流量design discharge设计水位design water level施工水位construction level；construction water level；working water level 设计洪水过程线designed flood hydrograph容许冲刷allowable scour一般冲刷general scour局部冲刷local scour；partial scour铁路测量railway survey线路踏勘；草测route reconnaissance初测preliminary survey定测location survey；alignment；final location survey导线测量traversing；traverse survey光电导线photoelectric traverse地形测量topographical survey横断面测量cross leveling；cross-section survey；cross-section leveling线路测量route survey；profile survey；longitudinal survey既有线测量；旧线测量survey of existing railway线路复测repetition survey of existing railway；resurvey of existing railway 测量精度survey precision；precision of survey均方差；中误差mean square error最大误差；极限误差maximum error；limiting error中线测量center line survey中线桩center line stake加桩additional stake；plus stake外移桩shift out stake；stake outward；offset stake水准点高程测量benchmark leveling中桩高程测量；中平center stake leveling曲线控制点curve control point放线setting-out of route；lay out of route交点intersection point副交点auxiliary intersection point转向角deflection angle分转向角auxiliary deflection angle坐标方位角plane-coordinate azimuth象限角quadrantal angle经纬距plane rectangular coordinate断链broken chain投影断链projection of broken chain断高broken height铁路航空摄影测量；铁路航测railway aerial photogrammetry铁路航空勘测railway aerial surveying航带设计flight strip design；design of flight strip铁路工程地质遥感remote sensing of railway engineering geology测段segment of survey航测选线aerial surveying alignment航测外控点field control point of aerophotogrammetry全球定位系统global positioning system；GPS像片索引图index of photography三角测量trigonometric survey；triangulation精密导线测量precise traverse survey；accurate traverse survey三角高程测量trigonometric leveling隧道洞外控制测量ouside tunnel control survey隧道洞内控制测量in tunnel control survey；through survey隧道洞口投点horizontal point of tunnel portal；geodetic control point of portal location of adit桥轴线测量survey of bridge axis铁路选线railway location；approximate railway location；location of railway route selection平原地区选线location in plain region；plain location越岭选线location of mountain line；location of line in mountain region；location over mountain山区河谷选线mountain and valley region location；location of line of in mountain and valley region丘陵地段选线hilly land location；location of line on hilly land工程地质选线engineering geoligic location of line线间距distance between centers of tracks；midway between tracks车站分布distribution of stations方案比选scheme comparison；route alternative投资回收期repayment period of capital cost纸上定线paper location of line缓坡地段section of easy grade；section of gentle slope紧坡地段section of sufficient grade非紧坡地段section of unsufficient grade；section fo insufficient grade导向线leading line；alignment guiding line拔起高度；克服高度height of lifting；lifting height；ascent of elevation横断面选线cross-section method of railway location；location with cross-section method；cross-section method for location of line展线extension of line；development of line；line development展线系数coefficient of extension line；coefficient of development line套线overlapping line线路平面图track plan；line plan线路纵断面图track profile；line profile站坪长度length of station site站坪坡度grade of station site控制区间control section；controlling section最小曲线半径minimum radius of curve圆曲线circular curve单曲线simple curve缓和曲线transition curve；easement curve；spiral transition curve缓和曲线半截变更率rate of easement curvature；rate of transition curve复曲线compound curve同向曲线curves of same sense；adjacent curves in one direction反向曲线reverse curve；curve of opposite sense夹直线intermediate straight line；tangent between curves坡度grade；gradient；slope人字坡double spur grade限制坡度ruling grade；limiting grade加力牵引坡度pusher grade；assisting grade最大坡度maximum grade临界坡度critical grade长大坡度long steep grade；long heavy grade动力坡度momentum grade均衡坡度balanced grade有害地段harmful district无害地段harmless district变坡点point of gradient change；breake in grade坡段grade section坡段长度length of grade section坡度差algebraic difference between adjacent gradients竖曲线vertical curve分坡平段level stretch between opposite sign gradient缓和坡度slight grade；flat grade；easy grade起动缓坡flat gradient for starting加速缓坡easy gradient for acceleration；accelerating grade坡度折减compensation of gradient；gradient compensation；grade compensation 曲线折减compensation of curve；curve compesation隧道坡度折减compensation of gradient in tunnel；compensation grade in tunnel 绕行地段detouring section；round section换侧；换边change side of double line容许应力设计法allowable stress design method破损阶段设计法plastic stage design method极限状态设计法limit state design method概率极限状态设计法；可靠度设计法probabilisatic limit state design method地震系数法seismic coefficient method路基subgrade；road bed；formation subgrade岩石路基rock subgrade渗水土路基permeable soil subgrade；pervious embankment非渗水土路基non-permeable soil subgrade；impervious embankment特殊土路基subgrade of special soil软土地区路基subgrade in soft soil zone；subgrade in soft；clay region泥沼地区路基subgrade in bog zone；subgrade in morass region；subgrade in swampland 膨胀土地区路基；裂土地区路基subgrade in swelling soil zone；subgrade in expansive soil region盐渍土地区路基subgrade in salty soil zone；subgrade in saline soil region多年冻土路基subgrade in permafrost soil zone特殊条件下的路基subgrade under special condition河滩路堤embankment on plain river beach滨河路堤embankment on river bank水库路基subgrade in reservoir；embankment crossing reservoir崩塌地段路基subgrade in rock fall district；subgrade in collapse zone岩堆地段路基subgrade in rock deposit zone；subgrade in talus zone；subgrade in scree zone滑坡地段路基subgrade in slide岩溶地段路基；喀斯特地段路基subgrade in karst zone洞穴地段路基subgrade in cavity zone；subgrade in cavern zone风沙地段路基subgrade in windy and sandy zone；subgrade in desert雪害地段路基subgrade in snow damage zone；subgrade in snow disaster zone泥石流地段路基subgrade in debris flow zone路基横断面subgrade cross-section路基面subgrade surface；formation路基面宽度width of the subgrade surface；formation width路拱road crown；subgrade crown路肩Road shoulder；subgrade shoulder路肩高程formation level；shoulder level路堤embankment；fill路堑cut；road；cutting半堤半堑part-cut and part-fill section；cut and fill section基床subgrade bed；formation基床表层surface layer of subgrade bed；formation top layer；surface layer of subgrade 基床表层bottom layer of subgrade；formation base layer；bottom layer of subgrade bed 一般路基general subgrade；ordinary subgrade最小填筑高度minimum fill height of subgrade；minimum height of fill临界高度critical height基底foundation base；base路堤边坡side slope of embankment；fill slope talus坡脚toe of side slope护道berm取土坑borrow pit路堤填料embankment fill material；embankment filler；filling material of embankment填料分类classification of filling material岩块填料rock block filler；rock filler；rock fill粗粒土填料coarse-grained soil filler；coarse-grained soil fill细粒土填料fine-grained soil filler；fine-grained soil fill压实标准compacting criteria相对密度relative density压实系数compacting factor；compacting coefficient最佳含水量optimum moisture content；best moisture content最佳密度optimum density；best density核子密度湿度测定determination of nuclear density-moisture路基承载板测定determination of bearing slab of subgrade预留沉落量reserve settlement；settlement allowance反压护道berm with superloading；berm for back pressure；counter swelling berm石灰砂桩lime sand pile换土change soil；soil replacement爆破排淤blasting discharging sedimentation；silt arresting by explosion；discharge of sedimentation by blasting抛石挤淤throwing stones to packing sedimentation；packing sedimentation by throwing stones；packing up sedimentation by dumping stones路堑石方爆破rock cutting blasting；rock blasting in cut定向爆破directional blasting浅孔爆破shallow hole blasting深孔爆破deep hole blasting洞室药包爆破chamber explosive package blasting；chamher blasting扬弃爆破abandoned blasting；abandonment blasting抛掷爆破pin-point blasting松动爆破blasting for loosening rock药壶爆破pot hole blasting裸露腰包爆破adobe blasting；contact blasting路堑边坡cutting slope；side slope of cut堑顶top of cutting slope；top of cutting路堑平台platform of cutting；berm in cutting弃土堆waste bank；bankette；spoil bank挡土墙retaining wall重力式挡土墙gravity retaining wall衡重式挡土墙balance weight retaining wall；gravity retaining wall with relieving platform；balanced type retaining wall锚定板挡土墙anchored retaining wall by tie rods；anchored bulkhead retaining wall；anchored plate retaining wall加筋土挡土墙reinforced earth retaining wall；reinforced soil retaining wall锚杆挡墙anchored bolt retaining wall；anchoraged retaining wall by tie rods管柱挡墙cylindrical shaft retaining wall沉井挡墙caisson retaining wall抗滑桩anti-slide pile；counter-sliding pile护墙guard wall护坡slope protection；revertment；pitching排水沟weep drain；drainage ditch；drain ditch边沟；侧沟side ditch天沟gutter；overhead ditch；intercepting ditch吊沟suspended ditch跌水hydraulic drop截水沟intercepting ditch；catch-drain急流槽chute排水槽drainage channel渗水暗沟blind drain渗水隧洞leak tunnel；permeable tunnel；drainage tunnel渗井leaching well；seepage well渗管leaky pipe平孔排水horizontal hole drainage反滤层reverse filtration layer；inverted filter；protective filter 检查井inspection well；manhole砂井；排水砂井sand drain隔断层insulating course；insulating layer透水路堤pervious embankment；permeable embankment渗水路堤immerseable embankment排水砂垫层sand filled drainage layer；drainage sand blanker坡面防护slope protection护岸revetment；shore protection导流堤diversion dike拦石墙stone cut off wall；stone falling wall；buttree落石槽stone falling channel；trough for catching falling rocks 柴排firewood raft；mattress；willow fascine固沙造林stabilization for sands by afforestation挡风墙wind-break wall防风栅栏wind break fence砂土液化sand liquefaction中-活载CR-live loading；China railway standard loading桥梁标准活载standard live load for bridge桥梁荷载谱bridge load spectrum换算均布活载equivalent uniform live load设计荷载design load主力principal load恒载dead load土压力earth load静水压力hydrostatic pressure浮力buoyancy列车活载live load of train列车离心力centrifugal force of train列车冲击力；冲击荷载impact force of train冲击系数ceofficient of impact人行道荷载sidewalk loading附加力subsidiary load；secondary load列车制动力braking force of train列车牵引力tractive force of train风荷载wind load列车横向摇摆力lateral swaying force of train流水压力pressure of water flow冰压力ice pressure冻胀力frost heaving force特殊荷载particular load船只或排筏的撞击力collision force of ship or raft地震力seismic force地震烈度earthquake intensity地震震级earthquake magnitude施工荷载constructional loading荷载组合loading conbination铁路桥railway bridge公铁两用桥combined bridge；combined highway and railway bridge；combined rail-cum-road bridge跨线桥；立交桥overpass bridge；grade separation bridge；flyover高架桥viaduct旱桥dry bridge人行桥foot bridge；pedestrian bridge圬工桥masonry bridge钢桥steel bridge铆接钢桥riveted steel bridge栓焊钢桥bolted and welded steel bridge全焊钢桥all welded steel bridge摩擦结合式高强度螺栓high strength friction grip bolt扭剪式高强度螺栓torshear type high strength blot螺栓示功扳手bolt wrench with indicator混凝土桥concrete bridge钢筋混凝土桥reinforced concrete bridge预应力混凝土桥prestressed concrete bridge先张法预应力梁pretensioned prestressed concrete girder后张法预应力梁post-tensioned prestressed concrete girder部分预应力混凝土桥partially prestressed concrete bridge结合梁桥composite beam bridge低高度梁shallow girder无碴无枕梁girder without ballast and sleeper型钢混凝土梁；劲性骨架混凝土梁girder with rolled steel section encased in concrete；skeleton reinforced concrete girder简支梁桥simply supported beam bridge连续梁桥continuous beam bridge悬臂梁桥cantilever beam bridge板桥slab bridge空心板桥hollow slab bridge板梁plate girder工形梁I-beam箱形梁box girder槽形梁trough girder桁架truss拆装式桁架demountable truss刚架桥；刚构桥rigid frame bridge斜腿刚架桥；斜腿刚构桥strutted beam bridge；slant-legged rigid frame bridge悬板桥；悬带桥stressed ribbon bridge悬索桥；吊桥suspension bridge斜拉桥cable-stayed bridge浮桥pontoon bridge；floating bridge；bateau bridge拱桥arch bridge固端拱；无铰拱fixed-end arch双铰拱two-hinged arch三铰拱three-hinged arch实腹拱spandrel-filled arch；solid-spandrel arch空腹拱open-spandrel arch双曲拱two-way curved arch；cross-curved arch系杆拱；柔性系杆刚性拱tied arch榔格尔式桥；刚性系杆柔性拱桥Langer bridge；flexible arch bridge with rigid tie洛泽式桥；直悬杆式刚性拱刚性梁桥Lohse bridge；rigid arch bridge with rigid tie and vertical sespenders尼尔森桥Nielsen systen bridge尼尔森式骆泽梁桥；斜悬杆式刚性拱梁桥Nielsen type Lhse bridge；rigid arch bridge with fighd tie and inclined suspenders活动桥movable bridge竖旋桥bascule bridge平旋桥swing bridge升降桥lift bridge正交桥right bridge斜交桥skew bridge曲线桥curved bridge曲梁curved beam特大桥super maior bridge大桥major bridge中桥medium bridge小桥minor bridge单线桥single track bridge双线桥double track bridge多线桥multi-track bridge正桥；主桥main bridge引桥approach spans上承式桥deck bridge半穿式桥；中承式half through bridge；midheight deck bridge 下承式桥through bridge双层桥double-deck bridge永久性桥permanent bridge临时性桥；便桥temporary bridge跨径；跨度span净跨clear spam桥梁全长overall length of bridge桥下净空underneath clearance主梁中心距center to center distance between main girder节间长度panel length梁高depth of girder拱度camber挠度deflection节间panel锚跨；锚孔anchor span悬跨；吊孔suspended span桥梁上部结构superstructure腹板web plate翼缘flange翼缘板flange plate弦杆chord member腹杆web member斜杆diagonal member竖杆vertical member吊杆suspender hanger加劲杆stiffener节点panel point节点板gusset plate拼接板splice plate缀条lacing bar缀板stay plate；tie plate侧向水平联结系lateral bracing横联sway bracing制动撑架braking bracing桥门架portal frame纵梁stringer横梁floor beam；transverse beam桥面系floor system端横梁end floor beam起重横梁jacking floor beam梁端缓冲梁auxiliary girder for controlling angle change 应变时效strain ageing碳当量carbon equivalent钢丝steel wire钢丝束bundled steel wires钢绞线steel strand钢筋reinforcement；steel bar箍筋stirrup纵向钢筋longitudinal reinforcement弯起钢筋bent-up bar架立钢筋erection bar构造钢筋constructional reinforcement预应力筋tendon套管sheath梁腋haunch拱圈arch ring拱肋arch rib拱顶rach crown拱矢rise of arch起拱点springing拱腹soffit拱腹线intrados拱背钱extrados桥塔bridge tower；pylon索平面cable plane缆索cable斜缆stay cable；inclined cable吊缆suspension cable索鞍cable saddle索夹cable band；cable clamp锚座socket锚碇anchorage明桥面open deck；ballastless deck；open floor桥梁道碴槽ballast trough道碴桥面ballasted deck；ballasted floor桥梁护轨guard rall of bridge桥梁护木guard timber of bridge桥枕bridge tie；bridge sleeper桥上人行道sidewalk on bridge步行板foot plank避车台refuge platform伸缩缝expansion joint正交异性板orthotropic plate栏杆railing；handrail；handrailing泻水孔drainage opening直结轨道track fastened directly to steel girders抗剪连接件；抗剪结合件shear connector支座bearing固定支座fixed bearing活动支座expension bearing；movable bearing平板支座plate bearing摇轴芝座rocker bearing滚轴支座roller bearing球面支座spherical bearing板式橡胶支座laminated rubber bearing盆式橡胶支座pot rubber bearing聚四氯乙烯支座poly-tetrafluoroedthylene bearing；PTFE bearing涡流激振wortex-excited oscillation弛振galloping颤振flutter扰流板spoiler风嘴wind fairing桥梁自振周期natural vibration period of bridge浮运架桥法bridge erection by floating架桥机架设法erection by bridge girder erecting equipment顶推式架设法erection by incremental launching拖拉架设法launching method赝架式架设法erection with scaffolding悬臂架设法catilever erection；erection by protrusion悬臂灌注法cast-in-place cantilever construction；free cantilever segmental concreting with suspended formwork悬臂拼装法cantilevered assembling constrution；free cantilever erection with segments of precast concrete预制混凝土构件precast concrete units；precast concrete members活动模架逐跨施工法segmental span-by-span construction using form traveller桥梁合龙closure就地贯注法cast-in-place method；cast-in-situ method活动吊篮travelling cradle顶进法jack-in method旋转法施工；转体施工erection by swing method液压式张拉千斤顶hydraulic tensioning jack桥梁下部结构substructure桥台abutment重力式桥台gravity abutment埋置式桥台buried abutment锚定板式桥台anchor slab abutmentU形桥台U-shaped abutment耳墙式桥台abutment with cantilevered retaining wall台身abutment body前墙front wall台帽abutment coping翼墙wing wall锥体护坡quadrant revetment；truncated cone banking台后填方filling behind abutment桥墩pier空心桥墩hollow pier实体桥墩solid pier重力式桥墩gravity pier柔性桥墩flexible pier拼装式桥墩assembly pier；pier constructed with precast units制动墩braking pier柱式桥墩column pierV形桥墩V-shaped pier圆端形桥墩round-ended pier圆形桥墩circular pier矩形桥墩rectangular pier排架式桥墩pile bent pier墩身pier body；pier shaft墩帽pier coping围栏railing around coping of pier or abutment承台bearing platform破冰体ice apron；ice-breaking cutwater；ice guard地基foundation；foundation soil；subgrade加固地基improved foundation；improved ground天然地基natural foundation；natural ground桥梁基础bridge foundation扩大基础spread foundation明挖基础open-cut foundation；open excavation foundation沉井基础open caisson foundation浮式沉井基础floating caisson foundation沉井刃脚cutting edge of open caisson围堰cofferdam双壁钢围堰钻孔基础double wall steel cofferdam bored foundation 预制钢壳钻孔基础prefabricated steel shell bored foundation泥浆套沉井法slurry jacket method for sinking caisson空气幕沉井法air curtain method for sinking caisson沉箱基础pneumatic caisson foundation管柱基础tubular column foundation桩基础pile foundation预制桩precast pile就地灌注桩cast-in-place concrete pile；cast-in-situ concrete pile螺旋喷射桩auger injected pile摩擦桩friction pile支承桩bearing pile钻孔桩bored pile挖孔桩dug pile钢桩steel pile钢管桩steel pipe pile钢板桩steel sheet pile板桩sheet pile木桩timber pile钢筋混凝土桩reinforced concrete pile砂桩sand pile挤密砂桩sand conpaction pile流砂quick sand；drift sand送桩pile follower试桩test pile斜桩batter pile；raking pile；spur pile护筒pile casting重锤夯实法heavy tamping method灰土换填夯实法mothod of lime-soil replacement and tamping灌注水下混凝土underwater concreting；concreting with tremie method 导流建筑物regulating structure丁坝；挑水坝spur dike顺坝longitudinal dam河床铺砌river bed paving码头wharf排架bent脚手架scaffold悬空脚手架hanging stage；hanging scaffold铁路涵洞railway culvert涵洞孔径aperture of culvert管涵pipe culvert箱涵box culvert拱涵arch culvert盖板涵slab culvert无压力涵洞inlet unsubmerged culvert压力式涵洞outlet submerged culvert半压力式涵洞inlet submerged culvert明渠open channel；open ditch；open drain倒虹吸管inverted siphon潮汐河流tidal river淤积silting；siltation流冰ice drift铁路轮渡railway car ferries轮渡站ferry station轮渡栈桥ferry trestle bridge渡轮ferry boat轮渡引线；轮渡斜引道ferry slip铁路隧道railway tunnel山岭隧道mountain tunnel越岭隧道over mountain line tunnel水下隧道；水地隧道subaqueous tunnel；underwater tunnel地铁隧道subway tunne；underground railway tunnel浅埋隧道shallow tunnel；shallow-depth tunnel；shallow burying tunnel 深埋隧道deep tunnel；deep-depth tunnel；deep burying tunnel单线隧道single track tunnel双线隧道double track tunnel多线隧道multiple track tunnel车站隧道station tunnel地铁车站subway station；metro station特长隧道super long tunnel长隧道long tunnel中长隧道medium tunnel短隧道short tunnel隧道群tunnel group地铁工程subway engineering；metro engineering洞口tunne ladit；tunnel opening隧道进口tunnel entrance隧道出口tunnel exit迎坡；正面坡front slope洞门tunnel portal洞门框tunnel portal frame端墙式洞门end wall tunnel portal柱式洞门post tunnel portal翼墙式洞门wing wall tunnel portal耳墙式洞门ear wall tunnel portal台阶式洞门bench tunnel portal正洞门orthonormal tunnel portal；straight tunnel portal斜洞门skew tunnel portal明洞门open-cut-tunnel portal；gallery portal衬砌lining拱圈arch边墙side wall仰拱invert；inverted arch底板floor整体式衬砌integral lining装配式衬砌precast lining；prefabricated lining。