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Air target intention recognition and causal effect analysis combining uncertainty information reasoning and potential outcome framework

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Chinese Journal of Aeronautics 2024年第1期37卷 287-299页

作者： Yu ZHANG Fanghui HUANG Xinyang DENG Mingda LI Wen JIANG School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710129China

Recognizing target intent is crucial for making decisions on the ***,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent recognition *** with the challenge,a target intention causal analysis paradigm is proposed by combining with an Intervention Retrieval(IR)model and a Hybrid Intention Recognition(HIR)*** target data acquired by the sensors are modelled as Basic Probability Assignments(BPAs)based on evidence theory to create uncertain ***,the HIR model is utilized to recognize intent for a tested sample from uncertain ***,the intervention operator under the evidence structure is utilized to perform attribute intervention on the tested *** retrieval is performed in the sample database based on the IR model to generate the intention distribution of the pseudo-intervention samples to analyze the causal effects of individual sample *** simulation results demonstrate that our framework successfully identifies the target intention under the evidence structure and goes further to analyze the causal impact of sample attributes on the target intention.

关键词： Causal effect analysis Hybrid intention recognition Intervention retrieval Target intention uncertainty reasoning

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Application of uncertainty reasoning Theory to Satellite Fault Detection and Diagnosis

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Engineering Sciences 2004年第1期 90-94页

作者： Yang Tianshe 1,2 , Li Huaizu 1, Sun Yanhong 2 (1. Management school, Xian Jiaotong University, Shanxi,Xian 710043 2. Xian Satellite Control Center of China, Shanxi, Xian 710043)

reasoning theories are divided into certainty reasoning theories and uncertainty reasoning theories. Now, only certainty reasoning theories are used to detect and diagnose satellite faults. However, in practice, it is difficult to detect and diagnose some faults of the satellite automatically only by use of certainty reasoning theories. The reason is that detection and diagnosis of these faults require a rational reasoning and a fault tolerant capability. Fortunately, uncertainty reasoning theories can meet these requirements. It is attracting attention of many experts in the space field all over the world that uncertainty reasoning theories are applied to detect and diagnose satellite faults. uncertainty reasoning theories include several kinds of theories, such as inclusion degree theory, rough set theory, evidence reasoning theory, probabilistic reasoning theory, fuzzy reasoning theory, and so on. Inclusion degree theory, rough set theory and evidence reasoning theory are three advanced ones. Based on these three theories respectively, the author introduces three new methods to detect and diagnose satellite faults in this paper. It is shown that the methods, suitable for detecting and diagnosing satellite faults, especially uncertainty faults, can remedy the defects of the current methods.

关键词： satellite fault detection diagnosis uncertainty reasoning

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The Study of Knowledge Representation and uncertainty reasoning for Computer Aided Failure Analysis Expert System

The Study of Knowledge Representation and Uncertainty Reason...

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2002年安全与科学技术国际会议

作者： LIU Xinling ZHANG Weifang GAO Wei & TAO Chunhu (Failure Analysis Center Beijing Institute of Aeronautical Materials Beijing 100095 China)andXU Yuanming (Department of Flight Vehicle Design and Applied Mechanics Beijing University of Aviation and Aerospace Beijing 100083 China)

＜正＞ Knowledge acquisition and representation of failure analysis as well as the reliability of conclusion are studied in this paper. The ways of knowledge acquisition and representation are given through the comparison of various knowledge acquisition algorithms and representation methods. The document-based processing algorithm is mainly used to acquire domain knowledge. The knowledge of failure analysis can be classified as the basic knowledge and case knowledge. Rules aided by procedural and object-oriented scheme are appropriate for representing the basic knowledge, and frame method for the failure case knowledge. The classical probability-based method is suitable for describing the strength of backward chaining rules, and certainty factor for describing the strength of forward chaining rules. As for the failure case knowledge, it is considered that case adaptation can incorporate the uncertainty reasoning.

关键词： failure analysis expert system knowledge acquisition and representation uncertainty reasoning

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Uncertain Knowledge reasoning Based on the Fuzzy Multi Entity Bayesian Networks

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Computers, Materials & Continua 2019年第7期61卷 301-321页

作者： Dun Li Hong Wu Jinzhu Gao Zhuoyun Liu Lun Li Zhiyun Zheng Zhengzhou University 100 Science AvenueZhengzhou450001China University of the Pacific 3601 Pacific AvenueStockton95211USA

With the rapid development of the semantic web and the ever-growing size of uncertain data,representing and reasoning uncertain information has become a great challenge for the semantic web application *** this paper,we present a novel reasoning framework based on the representation of fuzzy ***,the paper gives an overview of the previous research work on uncertainty knowledge representation and reasoning,incorporates Ontology into the fuzzy Multi Entity Bayesian Networks theory,and introduces fuzzy PR-OWL,an Ontology language based on *** PROWL describes fuzzy semantics and uncertain relations and gives grammatical definition and semantic ***,the paper explains the integration of the Fuzzy Probability theory and the Belief Propagation *** influencing factors of fuzzy rules are added to the belief that is propagated between the nodes to create a reasoning framework based on fuzzy *** that,the reasoning process,including the SSFBN structure algorithm,data fuzzification,reasoning of fuzzy rules,and fuzzy belief propagation,is ***,compared with the classical algorithm from the aspect of accuracy and time complexity,our uncertain data representation and reasoning method has higher accuracy without significantly increasing time complexity,which proves the feasibility and validity of our solution to represent and reason uncertain information.

关键词： Ontology language uncertainty representation uncertainty reasoning fuzzy multi entity Bayesian networks belief propagation algorithm fuzzy PR-OWL

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一个基于不确定性推理的网络安全评估模型

一个基于不确定性推理的网络安全评估模型

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2006年全国理论计算机科学学术年会

作者：王维锋刘海燕霍景河装甲兵工程学院信息工程系装甲兵工程学院信息工程系装甲兵工程学院信息工程系

＜正＞1 引言网络安全性能的评估是信息系统的一个重要评价指标。由于网络系统的复杂性以及网络应用的多样性,网络系统的安全性成为一个由不确定性知识和经验性知识组成的复杂知识体系。人工智能中的

关键词： Security evaluation uncertainty reasoning Uncertain knowledge Scan

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The Research of Emotional Cognition Model Which Based On Bayesian Network within Intelligent Tutoring System

The Research of Emotional Cognition Model Which Based On Bay...

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2009 International Conference on Computational Intelligence and Natural Computing(CINC 2009)

作者： Jianghua Liu1 Wansen Wang1 1. Information Engineering College Capital Normal University Beijing China

Against the defects of the traditional intelligent network tutoring system in the emotion of teaching, the paper presents a new intelligent tutoring system structure which based on emotional cognition model, and solved the uncertainty reasoning problems within the process of emotional teaching effectively through the inference engine which based on Bayesian network. The simulation results show that the model can be used to apply to the personalized intelligent network teaching system very well which based on the interactive of emotion and cognition.

关键词： intelligent tutoring system learning emotion emotional cognition Bayesian network uncertainty reasoning educational psychology.

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Focused Web Crawling Strategy Based on Concept Context Graph

Focused Web Crawling Strategy Based on Concept Context Graph

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第四届全国信息检索与内容安全学术会议

作者： YaJun Du~(12) ZhanBing Dong~1 YuTing Wang~1 ~1 School of Mathematical and Computers Science,Xihua University,Chengdu 610039,Sichuan,China

With Internet growing exponentially,search engine is encountering some unprecedented *** focused search engine is to selectively seek out Web pages that are relevant to user topics;it can improve precision and refreshing speed for retrieving Web *** so,in order to obtain a high crawling efficiency,it is crucial and popspot research what strategy is utilized to visit Web for the focused search *** this paper,by researching the characteristics of current focused Web crawling strategies,the top-specific crawling on the Web with the measurements of the concept context graph is brought *** main contributions are listed as follows:to study hierarchy semantic relation among concepts of concept lattice,to define core concept and non core concept;to propose a novel notion representing user interest topic model with the＄FCA＄(Formal Concept Analysis);to propose how to compute concept semantic distance and concept semantic similarity for constructing the concept context *** matching unvisited Web pages with concept lattice of the user interest topic,to pick out relevant hyperlink,the ranking of the unvisited Web page is *** the other hand,the focused web crawling system based on FCA is *** experiments illuminates that precision,recall,average harvest rate,and F-Measure of our method outperform context graph,relevancy context graph,and breadth first crawling. We compare and evaluate the impacts of three similarity functions-liner,square,exponential similarity function to our method,and make a conclusion:the faster the similarity function decrease,the finer it not always impacts the crawling performance.

关键词： Search Engine Concept Lattice Association Rule uncertainty reasoning Web Page Matching Algorithm

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