Review on inferential situation models

Introduction to Artificial Intelligence智慧树知到课后章节答案2023年下哈尔滨工程大学哈尔滨工程大学第一章测试1.All life has intelligence The following statements about intelligence arewrong（）A:All life has intelligence B:Bacteria do not have intelligence C:At present,human intelligence is the highest level of nature D:From the perspective of life, intelligence is the basic ability of life to adapt to the natural world答案:Bacteria do not have intelligence2.Which of the following techniques is unsupervised learning in artificialintelligence?（）A:Neural network B:Support vector machine C:Decision tree D:Clustering答案:Clustering3.To which period can the history of the development of artificial intelligencebe traced back?（）A:1970s B:Late 19th century C:Early 21st century D:1950s答案:Late 19th century4.Which of the following fields does not belong to the scope of artificialintelligence application?（）A:Aviation B:Medical C:Agriculture D:Finance答案:Aviation5.The first artificial neuron model in human history was the MP model,proposed by Hebb.（）A:对 B:错答案:错6.Big data will bring considerable value in government public services, medicalservices, retail, manufacturing, and personal location services. （）A:错 B:对答案:对第二章测试1.Which of the following options is not human reason:（）A:Value rationality B:Intellectual rationality C:Methodological rationalityD:Cognitive rationality答案:Intellectual rationality2.When did life begin? （）A:Between 10 billion and 4.5 billion years B:Between 13.8 billion years and10 billion years C:Between 4.5 billion and 3.5 billion years D:Before 13.8billion years答案:Between 4.5 billion and 3.5 billion years3.Which of the following statements is true regarding the philosophicalthinking about artificial intelligence?（）A:Philosophical thinking has hindered the progress of artificial intelligence.B:Philosophical thinking has contributed to the development of artificialintelligence. C:Philosophical thinking is only concerned with the ethicalimplications of artificial intelligence. D:Philosophical thinking has no impact on the development of artificial intelligence.答案:Philosophical thinking has contributed to the development ofartificial intelligence.4.What is the rational nature of artificial intelligence?（）A:The ability to communicate effectively with humans. B:The ability to feel emotions and express creativity. C:The ability to reason and make logicaldeductions. D:The ability to learn from experience and adapt to newsituations.答案:The ability to reason and make logical deductions.5.Which of the following statements is true regarding the rational nature ofartificial intelligence?（）A:The rational nature of artificial intelligence includes emotional intelligence.B:The rational nature of artificial intelligence is limited to logical reasoning.C:The rational nature of artificial intelligence is not important for itsdevelopment. D:The rational nature of artificial intelligence is only concerned with mathematical calculations.答案:The rational nature of artificial intelligence is limited to logicalreasoning.6.Connectionism believes that the basic element of human thinking is symbol,not neuron; Human's cognitive process is a self-organization process ofsymbol operation rather than weight. （）A:对 B:错答案:错第三章测试1.The brain of all organisms can be divided into three primitive parts:forebrain, midbrain and hindbrain. Specifically, the human brain is composed of brainstem, cerebellum and brain (forebrain). （）A:错 B:对答案:对2.The neural connections in the brain are chaotic. （）A:对 B:错答案:错3.The following statement about the left and right half of the brain and itsfunction is wrong （）.A:When dictating questions, the left brain is responsible for logical thinking,and the right brain is responsible for language description. B:The left brain is like a scientist, good at abstract thinking and complex calculation, but lacking rich emotion. C:The right brain is like an artist, creative in music, art andother artistic activities, and rich in emotion D:The left and right hemispheres of the brain have the same shape, but their functions are quite different. They are generally called the left brain and the right brain respectively.答案:When dictating questions, the left brain is responsible for logicalthinking, and the right brain is responsible for language description.4.What is the basic unit of the nervous system?（）A:Neuron B:Gene C:Atom D:Molecule答案:Neuron5.What is the role of the prefrontal cortex in cognitive functions?（）A:It is responsible for sensory processing. B:It is involved in emotionalprocessing. C:It is responsible for higher-level cognitive functions. D:It isinvolved in motor control.答案:It is responsible for higher-level cognitive functions.6.What is the definition of intelligence?（）A:The ability to communicate effectively. B:The ability to perform physicaltasks. C:The ability to acquire and apply knowledge and skills. D:The abilityto regulate emotions.答案:The ability to acquire and apply knowledge and skills.第四章测试1.The forward propagation neural network is based on the mathematicalmodel of neurons and is composed of neurons connected together by specific connection methods. Different artificial neural networks generally havedifferent structures, but the basis is still the mathematical model of neurons.（）A:对 B:错答案:对2.In the perceptron, the weights are adjusted by learning so that the networkcan get the desired output for any input. （）A:对 B:错答案:对3.Convolution neural network is a feedforward neural network, which hasmany advantages and has excellent performance for large image processing.Among the following options, the advantage of convolution neural network is（）.A:Implicit learning avoids explicit feature extraction B:Weight sharingC:Translation invariance D:Strong robustness答案:Implicit learning avoids explicit feature extraction;Weightsharing;Strong robustness4.In a feedforward neural network, information travels in which direction?（）A:Forward B:Both A and B C:None of the above D:Backward答案:Forward5.What is the main feature of a convolutional neural network?（）A:They are used for speech recognition. B:They are used for natural languageprocessing. C:They are used for reinforcement learning. D:They are used forimage recognition.答案:They are used for image recognition.6.Which of the following is a characteristic of deep neural networks?（）A:They require less training data than shallow neural networks. B:They havefewer hidden layers than shallow neural networks. C:They have loweraccuracy than shallow neural networks. D:They are more computationallyexpensive than shallow neural networks.答案:They are more computationally expensive than shallow neuralnetworks.第五章测试1.Machine learning refers to how the computer simulates or realizes humanlearning behavior to obtain new knowledge or skills, and reorganizes the existing knowledge structure to continuously improve its own performance.（）A:对 B:错答案:对2.The best decision sequence of Markov decision process is solved by Bellmanequation, and the value of each state is determined not only by the current state but also by the later state.（）A:对 B:错答案:对3.Alex Net's contributions to this work include: （）.A:Use GPUNVIDIAGTX580 to reduce the training time B:Use the modified linear unit (Re LU) as the nonlinear activation function C:Cover the larger pool to avoid the average effect of average pool D:Use the Dropouttechnology to selectively ignore the single neuron during training to avoid over-fitting the model答案:Use GPUNVIDIAGTX580 to reduce the training time;Use themodified linear unit (Re LU) as the nonlinear activation function;Cover the larger pool to avoid the average effect of average pool;Use theDropout technology to selectively ignore the single neuron duringtraining to avoid over-fitting the model4.In supervised learning, what is the role of the labeled data?（）A:To evaluate the model B:To train the model C:None of the above D:To test the model答案:To train the model5.In reinforcement learning, what is the goal of the agent?（）A:To identify patterns in input data B:To minimize the error between thepredicted and actual output C:To maximize the reward obtained from theenvironment D:To classify input data into different categories答案:To maximize the reward obtained from the environment6.Which of the following is a characteristic of transfer learning?（）A:It can only be used for supervised learning tasks B:It requires a largeamount of labeled data C:It involves transferring knowledge from onedomain to another D:It is only applicable to small-scale problems答案:It involves transferring knowledge from one domain to another第六章测试1.Image segmentation is the technology and process of dividing an image intoseveral specific regions with unique properties and proposing objects ofinterest. In the following statement about image segmentation algorithm, the error is （）.A:Region growth method is to complete the segmentation by calculating the mean vector of the offset. B:Watershed algorithm, MeanShift segmentation,region growth and Ostu threshold segmentation can complete imagesegmentation. C:Watershed algorithm is often used to segment the objectsconnected in the image. D:Otsu threshold segmentation, also known as themaximum between-class difference method, realizes the automatic selection of global threshold T by counting the histogram characteristics of the entire image答案:Region growth method is to complete the segmentation bycalculating the mean vector of the offset.2.Camera calibration is a key step when using machine vision to measureobjects. Its calibration accuracy will directly affect the measurementaccuracy. Among them, camera calibration generally involves the mutualconversion of object point coordinates in several coordinate systems. So,what coordinate systems do you mean by "several coordinate systems" here?（）A:Image coordinate system B:Image plane coordinate system C:Cameracoordinate system D:World coordinate system答案:Image coordinate system;Image plane coordinate system;Camera coordinate system;World coordinate systemmonly used digital image filtering methods:（）.A:bilateral filtering B:median filter C:mean filtering D:Gaussian filter答案:bilateral filtering;median filter;mean filtering;Gaussian filter4.Application areas of digital image processing include:（）A:Industrial inspection B:Biomedical Science C:Scenario simulation D:remote sensing答案:Industrial inspection;Biomedical Science5.Image segmentation is the technology and process of dividing an image intoseveral specific regions with unique properties and proposing objects ofinterest. In the following statement about image segmentation algorithm, the error is ( ).A:Otsu threshold segmentation, also known as the maximum between-class difference method, realizes the automatic selection of global threshold T by counting the histogram characteristics of the entire imageB: Watershed algorithm is often used to segment the objects connected in the image. C:Region growth method is to complete the segmentation bycalculating the mean vector of the offset. D:Watershed algorithm, MeanShift segmentation, region growth and Ostu threshold segmentation can complete image segmentation.答案:Region growth method is to complete the segmentation bycalculating the mean vector of the offset.第七章测试1.Blind search can be applied to many different search problems, but it has notbeen widely used due to its low efficiency.（）A:错 B:对答案:对2.Which of the following search methods uses a FIFO queue （）.A:width-first search B:random search C:depth-first search D:generation-test method答案:width-first search3.What causes the complexity of the semantic network （）.A:There is no recognized formal representation system B:The quantifiernetwork is inadequate C:The means of knowledge representation are diverse D:The relationship between nodes can be linear, nonlinear, or even recursive 答案:The means of knowledge representation are diverse;Therelationship between nodes can be linear, nonlinear, or even recursive4.In the knowledge graph taking Leonardo da Vinci as an example, the entity ofthe character represents a node, and the relationship between the artist and the character represents an edge. Search is the process of finding the actionsequence of an intelligent system.（）A:对 B:错答案:对5.Which of the following statements about common methods of path search iswrong（）A:When using the artificial potential field method, when there are someobstacles in any distance around the target point, it is easy to cause the path to be unreachable B:The A* algorithm occupies too much memory during the search, the search efficiency is reduced, and the optimal result cannot beguaranteed C:The artificial potential field method can quickly search for acollision-free path with strong flexibility D:A* algorithm can solve theshortest path of state space search答案:When using the artificial potential field method, when there aresome obstacles in any distance around the target point, it is easy tocause the path to be unreachable第八章测试1.The language, spoken language, written language, sign language and Pythonlanguage of human communication are all natural languages.（）A:对 B:错答案:错2.The following statement about machine translation is wrong （）.A:The analysis stage of machine translation is mainly lexical analysis andpragmatic analysis B:The essence of machine translation is the discovery and application of bilingual translation laws. C:The four stages of machinetranslation are retrieval, analysis, conversion and generation. D:At present,natural language machine translation generally takes sentences as thetranslation unit.答案:The analysis stage of machine translation is mainly lexical analysis and pragmatic analysis3.Which of the following fields does machine translation belong to? （）A:Expert system B:Machine learning C:Human sensory simulation D:Natural language system答案:Natural language system4.The following statements about language are wrong: （）。

从关联理论的角度看翻译中的语境问题从关联理论的角度看翻译中的语境问题[Abstract]Sperber and Wilson first put forward the Relevance Theory, which explains linguistic activities in the framework of cognition. Their student Ernst-August Gutt applied it to translation studies and got an encouraging result. He pointed out that translation is not only a communicative activity, but also a cognitive activity. Context plays a very important role in our understanding of the utterance and text. A successful translation requires the translator to reason according to the dynamic context, which depends so much on the relevance of the language and environment. In fact, the process of translation is a process of context reasoning and selecting, which is always dynamic and developing as the circumstances change. During the process of translation, the main task of translator is to find out the relevance, especially the optimal relevancebetween the language and context. According to the principle of the optimal relevance, the translator could understand the original text correctly, and then translate it into target language appropriately by composing and reasoning the most suitable context. Discussing on context in the perspective of relevance theory provides a new view to study and practice translation.[Key Words] Translation; communication; relevance theory; optimal relevance; cognitive context; dynamic context【摘要】关联理论是由Sperber and Wilson 最早提出的，它从认知的角度解释了许多的语言活动。

湖 南 涉 外 经 济 学 院本科毕业论文（设计）（页面设置：论文页边距：上30mm ，下25mm ，左25mm ，右25mm ，页眉20 mm 、页脚15 mm ）题目作者学院专业学号指导教师 二〇一六年五月三日论文诚信声明示例（打印时删除蓝色字）湖南涉外经济学院本科毕业论文（设计）诚信声明本人声明：所呈交的本科毕业论文（设计），是本人在指导老师的指导下，独立开展工作所取得的成果，成果不存在知识产权争议，除文中已经注明引用的内容外，本论文不含任何其他个人或集体已经发表或创作过的作品成果。

对本文工作做出重要贡献的个人和集体均已在文中以明确方式标明。

本人完全意识到本声明的法律结果由本人承担。

本科毕业论文（设计）作者签名：（手写）二○一六年五月三日（打印）The thesis mainly analyzes the roots of the tragic fate of the heroine—Margaret. At the beginning of the thesis, the author introduces the background of Alexandre Dumas Fills and his masterpiece –Camellias, which is a love tragedy on the basis of his life experiences, making great influence on many a people. And then, the author introduces the typical tragic character, Margret’s miserable fortune and the roots. To make the theme outstanding, the author illustrates the painful sufferings of Margret in society, culture, characteristics, love and religious persecution in detail. Finally, let’s come to the conclusion that female should improve the conscious of self—awareness, have the control of our own fates, be brave to fightKeywords: Margret; tragic fate; reasons本文主要分析了女主人公玛格丽特的悲剧命运及其根源。

Situational Awareness Using DBSCAN in Smart-Grid Ranganath Vallakati;Anupam Mukherjee;Prakash Ranganathan【期刊名称】《智能电网与可再生能源（英文）》【年(卷),期】2015(6)5【摘要】Synchrophasors are the state-of-the-art measuring devices that sense various parameters such as voltage, current, frequency, and other grid parameters with a high sampling rate. This paper presents an approach to visualize and analyze the smart-grid data generated by synchrophasors using a visualization tool and density based clustering technique. A MATLAB based circle representation tool is utilized to visualize the real-time phasor data generated by a smart-grid model that mimics a synchrophasor. A density based clustering technique is also used to cluster the phasor data with the aim to detect contingency situations such as bad-data classification, various fault types, deviation on frequency, voltage or current values for better situational alertness. The paper uses data from an IEEE fourteen bus system test-bed modeled inMATLAB/SIMULINK to aid system operators in carrying various predictive analytics, and decisions.【总页数】8页(P120-127)【关键词】Clustering;Density;Based;Clustering;(DBSCAN);IEEE;Test-Bed;Phasor;Measurement;Unit;Visualization【作者】Ranganath Vallakati;Anupam Mukherjee;Prakash Ranganathan 【作者单位】Department of Electrical Engineering, University of North Dakota, Grand Forks, USA【正文语种】中文【中图分类】R73【相关文献】1.A scalable model for network situational awareness based on Endsley＇s situation model [J], 胡威;Li Jianhua;Chen Xiuzhen;Jiang Xinghao;Zuo Min2.A scalable model for network situational awareness based on Endsley's situation model [J], Hu Wei; Li Jianhua; Chen Xiuzhen; Jiang Xinghao; Zuo Min3.Evaluation of the situational awareness effects for smart distribution networks under the novel design of indicator framework and hybrid weighting method [J], Leijiao GE;Yuanliang LI;Suxuan LI;Jiebei ZHU;Jun YAN4.Concept and Research Framework for Coordinated Situation Awareness and Active Defense of Cyber-physical Power Systems Against Cyber-attacks [J], Ming Ni;Manli Li;Jun’e Li;Yingjun Wu;Qi Wang5.Review on strategies of space-based optical space situational awareness [J], HU Yunpeng;LI Kebo;LIANG Yan'gang;CHEN Lei因版权原因，仅展示原文概要，查看原文内容请购买。

《多模态深度学习综述》篇一一、引言随着信息技术的飞速发展，人类正面临着一个多元、异构、复杂的数据世界。

在这个世界中，多模态数据因其丰富的信息表达和多样的数据来源，正逐渐成为人工智能领域的研究热点。

多模态深度学习作为处理多模态数据的有效手段，其研究与应用日益广泛。

本文旨在全面回顾多模态深度学习的研究现状，总结其关键技术和发展趋势，以期为后续研究者提供参考。

二、多模态深度学习的定义与分类多模态深度学习是一种融合多种模态数据，通过深度学习技术进行特征提取、表示学习和任务求解的方法。

多模态数据包括但不限于文本、图像、音频、视频等，这些不同模态的数据在信息表达和感知方式上具有互补性。

根据应用场景和任务需求，多模态深度学习可分为跨模态检索、多模态融合、多模态生成等。

三、多模态深度学习的关键技术1. 数据预处理：在多模态数据处理过程中，需要对不同模态的数据进行预处理，包括数据清洗、特征提取、数据对齐等。

这些预处理步骤对于提高多模态深度学习的性能至关重要。

2. 特征表示：特征表示是多模态深度学习的核心任务之一。

通过深度学习技术，可以将不同模态的数据映射到同一特征空间，实现跨模态的语义理解和信息交互。

3. 融合策略：多模态融合策略包括早期融合、晚期融合和混合融合等。

早期融合主要在数据预处理阶段进行融合，晚期融合则是在特征或决策层面进行融合。

混合融合则结合了早期和晚期融合的优点，根据任务需求灵活调整融合策略。

4. 模型训练：多模态深度学习需要设计合适的模型结构和训练方法。

常用的模型包括循环神经网络、卷积神经网络、生成对抗网络等。

针对多模态数据的特性，需要设计具有跨模态交互能力的模型结构，并采用合适的优化算法进行训练。

四、多模态深度学习的应用领域多模态深度学习在各个领域都有广泛的应用，包括但不限于以下方面：1. 图像与文本的跨模态检索：通过多模态深度学习技术，实现图像与文本之间的跨模态检索，提高检索的准确性和效率。

2. 人机交互：多模态深度学习可以实现在自然语言处理、语音识别、手势识别等多模态信息的融合和处理，提高人机交互的智能性和便捷性。

高一人工智能英语阅读理解25题1<背景文章>Artificial intelligence (AI) has become one of the most talked - about topics in recent years. AI can be defined as the simulation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning, problem - solving, perception, and language understanding.The development of AI has a long history. It started in the 1950s when the concept was first introduced. In the early days, AI research focused on simple tasks like playing games and solving basic mathematical problems. However, with the development of computer technology and the increase in data availability, AI has made great strides.AI has found applications in various fields. In the medical field, AI can assist doctors in diagnosing diseases. For example, it can analyze medical images such as X - rays and MRIs to detect early signs of diseases that might be missed by human eyes. In education, AI - powered tutoring systems can provide personalized learning experiences for students. They can adapt to the individual learning pace and style of each student, helping them to better understand difficult concepts. In the transportation industry, self - driving cars, which are a significant application of AI, are expectedto revolutionize the way we travel. They can potentially reduce traffic accidents caused by human error and improve traffic efficiency.However, AI also brings some potential negative impacts. One concern is the impact on employment. As AI systems can perform many tasks that were previously done by humans, there is a fear that many jobs will be lost. For example, jobs in manufacturing, customer service, and some administrative tasks may be at risk. Another issue is the ethical considerations. For instance, how should AI make decisions in life - or - death situations? And there are also concerns about data privacy as AI systems rely on large amounts of data.1. <问题1>What is the main idea of this passage?A. To introduce the development of computer technology.B. To discuss the applications and impacts of artificial intelligence.C. To explain how to solve problems in different fields.D. To show the importance of data in AI systems.答案：B。

《多模态深度学习综述》篇一一、引言随着信息时代的到来，人工智能、大数据等领域的迅速发展，单一模式的信息处理已经难以满足现代技术的需求。

其中，多模态深度学习成为了跨领域、跨媒体、跨信息类型研究的热点问题。

本综述将就多模态深度学习的定义、方法、研究进展及其在各个领域的应用进行综合概述，并讨论目前面临的主要挑战与未来发展方向。

二、多模态深度学习定义及理论基础1. 定义：多模态深度学习是深度学习的一个子集，指运用多种形式的感知数据进行数据理解和模型学习的技术。

这些感知数据可以是图像、文本、音频、视频等不同类型的数据。

2. 理论基础：多模态深度学习基于神经网络理论，通过深度学习算法对不同模态的数据进行特征提取和融合，以实现跨模态信息的处理和理解。

三、多模态深度学习方法1. 数据融合方法：在多模态深度学习中，数据融合是一个重要的步骤。

其主要目的是将来自不同模态的数据进行有效的整合和利用。

常见的融合方法包括早期融合、中期融合和晚期融合等。

2. 模型训练方法：在多模态深度学习中，常用的模型训练方法包括多任务学习、联合学习和迁移学习等。

这些方法旨在提高模型的泛化能力和鲁棒性，使得模型可以更好地处理和理解多模态数据。

四、多模态深度学习在各领域的应用1. 图像-文本分析：如新闻推送、商品推荐等需要分析图像和文本的场景中，多模态深度学习可以通过结合图像和文本信息，提高理解和推理的准确性。

2. 语音-语言处理：在语音识别、机器翻译等领域，多模态深度学习可以通过融合语音和语言信息，提高系统的准确性和效率。

3. 视频分析：在视频监控、自动驾驶等领域，多模态深度学习可以通过分析视频中的图像、音频和文本等信息，实现更精确的场景理解和预测。

五、研究进展与挑战近年来，多模态深度学习在理论研究和应用方面都取得了显著的进展。

然而，仍面临许多挑战和问题，如不同模态数据间的语义鸿沟、模型泛化能力等问题。

为了解决这些问题，未来的研究需要关注以下方向：1. 模型结构优化：需要设计更加灵活、可解释性更强的多模态深度学习模型，以提高模型的性能和鲁棒性。