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Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference最新文献

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Soundness and completeness theorems between the Dempster-Shafer theory and logic of belief 邓普斯特-谢弗理论与信念逻辑之间的完备性定理
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343847
T. Murai, M. Miyakoshi, M. Shimbo
{"title":"Soundness and completeness theorems between the Dempster-Shafer theory and logic of belief","authors":"T. Murai, M. Miyakoshi, M. Shimbo","doi":"10.1109/FUZZY.1994.343847","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343847","url":null,"abstract":"Modelling of belief is one of most important issues in intelligent systems. Roughly speaking, one can find two approaches in the literature: one is a logical approach using modal logic; the other is a numerical approach such as Bayesian theory, Dempster-Shafer theory of evidence (or D-S theory). The former is mainly concerned with logical inference methodology with belief, while the latter is mainly concerned with belief formation using methods of updating such as conditional probability and Dempster's rule of combination. Since characteristics of the two approaches are complementary to each other, one would have a more effective method of dealing with belief if they were unified. However, there are few studies of theoretical relationship connecting the two approaches. The purpose of this paper is to present a basis for unifying modal-logical and D-S-theory-based approaches by means of proving soundness and completeness theorems of several systems of modal logic with respect to classes of belief-function-based and plausibility-function-based models newly defined in this paper. The result shows that modal-logical structure is intrinsic in D-S theory, and would enable one (1) to introduce a concept of belief formation based on aggregation of evidence into a modal-logical approach to belief, (2) to decide rules of inference which are valid under available uncertain evidence, and (3) to introduce a concept of knowledge acquisition from a logical point of view into a belief formation method in D-S theory.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122696649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 18
A mathematical formulation of hierarchical systems using fuzzy logic systems 使用模糊逻辑系统的层次系统的数学公式
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343695
Li-Xin Wang
{"title":"A mathematical formulation of hierarchical systems using fuzzy logic systems","authors":"Li-Xin Wang","doi":"10.1109/FUZZY.1994.343695","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343695","url":null,"abstract":"In this paper, we use fuzzy logic systems to model higher levels of hierarchical systems. Specifically, we consider three-level hierarchical systems where the lowest level comprises the plant and convertional feedback controllers, the middle level performs supervisory operations to guarantee the stability of the whole system, and the top level is a planning level which provides control targets for the lower levels and communicates with the environment. The plant is modeled by differential equations, and the supervision and planning levels are modeled by fuzzy logic systems. The advantage of this model is that all the levels are formulated in a same mathematical framework (due to the dual role of fuzzy logic systems), therefore it is possible to analyze the hierarchical systems in a mathematically rigorous fashion. Two case studies are presented: integrated planning and control of mobile robots, and intelligent vehicle/highway systems.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123901658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Medical expert system with elastic fuzzy logic 基于弹性模糊逻辑的医学专家系统
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343547
H. C. Tseng, D.W. Teo
{"title":"Medical expert system with elastic fuzzy logic","authors":"H. C. Tseng, D.W. Teo","doi":"10.1109/FUZZY.1994.343547","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343547","url":null,"abstract":"We investigate the use of elastic fuzzy logic in a typical medical diagnosis. Fuzzy rules are formulated using common symptoms as antecedents and diagnoses as consequents. Different weighting factors on antecedents are assigned in each rule. This is done to better reflect the fact that in most diagnoses, there are major symptoms among all related symptoms. We also formulated a geometry-mean fuzzification scheme in issuing final decisions. A multiple-pass interactive scheme to retrieve symptom descriptions from patients is used to capture more realistic diagnosis information. An internal medicine expert system with the proposed framework is used to illustrate our design.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125410839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 17
Hybrid fuzzy neural nets are universal approximators 混合模糊神经网络是一种通用逼近器
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343759
J. Buckley, U. Hayashi
{"title":"Hybrid fuzzy neural nets are universal approximators","authors":"J. Buckley, U. Hayashi","doi":"10.1109/FUZZY.1994.343759","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343759","url":null,"abstract":"It is known that regular fuzzy neural nets, based on standard fuzzy arithmetic and the extension principle, can not be universal approximators. This negative result is surprising since (regular) neural nets are universal approximators. We argue that hybrid fuzzy neural nets, not necessarily based only on standard fuzzy arithmetic, can be universal approximators.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125425389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 13
A preliminary study of hybrid fuzzy/statistically-based controllers 模糊/统计混合控制器的初步研究
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343725
A. Wright, P. Ralston
{"title":"A preliminary study of hybrid fuzzy/statistically-based controllers","authors":"A. Wright, P. Ralston","doi":"10.1109/FUZZY.1994.343725","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343725","url":null,"abstract":"This paper describes the development and preliminary analysis of hybrid fuzzy/statistically-based controllers, including Fuzzy CUSUM. The Fuzzy CUSUM controller is a modification of a CUSUM type controller developed from statistical quality control concepts with fuzzy elements added. These controllers may be used in several process applications, especially the quality control of batch operations. First, the original controller is described and its performance evaluated. Next, the fuzzy elements are added to the controller and its performance is detailed. A completely randomized block experimental design and Duncan's multiple range test are used to compare the hybrid controllers to other types of controllers currently being explored, under a variety of disturbance conditions. The hybrid fuzzy/statistically-based controllers significantly outperform all other controllers examined.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129855009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Incorporating cell map information in fuzzy controller design 在模糊控制器设计中引入细胞图信息
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343665
He Hu, H. Tai, S. Shenoi
{"title":"Incorporating cell map information in fuzzy controller design","authors":"He Hu, H. Tai, S. Shenoi","doi":"10.1109/FUZZY.1994.343665","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343665","url":null,"abstract":"Cell mapping is a powerful mechanism for evaluating the global behavior of nonlinear dynamical systems. A cell map conveys direct information about system dynamics, including the regions of stability, the set of controllable initial states and system trajectories. This paper shows how cell map information can be incorporated in a genetic algorithm for tuning fuzzy controller parameters. The resulting fuzzy controller exhibits superior performance to controllers designed using conventional techniques. It has near time-optimal characteristics with maximal stability and controllability.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129644640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 26
A fuzzy object oriented data model 一个模糊的面向对象的数据模型
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343626
Gloria Bordogna, D. Lucarella, G. Pasi
{"title":"A fuzzy object oriented data model","authors":"Gloria Bordogna, D. Lucarella, G. Pasi","doi":"10.1109/FUZZY.1994.343626","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343626","url":null,"abstract":"The increasing complexity of real applications in the field of multimedia information systems requires the enhancement of modelling capabilities of object oriented data models (OODMs) in order to deal with imprecise and uncertain data. Some fuzzy extensions of the OODMs have been proposed in the literature, in which imprecision and uncertainty are managed at the level of object attributes and relations. What is still lacking is a unifying and systematic formalization of these extensions. In this contribution, starting from an existing graph-based-object model, the authors propose a fuzzy object oriented data (FOOD) model for the management of imprecise data.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"329 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124646078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 69
Defuzzification based on fuzzy clustering 基于模糊聚类的去模糊化
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343943
H. Genther, T. Runkler, M. Glesner
{"title":"Defuzzification based on fuzzy clustering","authors":"H. Genther, T. Runkler, M. Glesner","doi":"10.1109/FUZZY.1994.343943","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343943","url":null,"abstract":"We develop a modified fuzzy clustering algorithm for parametric defuzzification in fuzzy rule base systems. Using examples and basic defuzzification properties we compare defuzzification by clustering with the standard defuzzification methods COG (Center of Gravity) and MOM (Mean of Maxima). Concerning fuzzy sets with forbidden zones the new method proves to be superior. We present how heuristic preprocessing and quality measures are used for appropriate parameter selection.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127681821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 24
Alternative fuzzy controller logics 备选模糊控制器逻辑
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343929
B. Schott, T. Whalen
{"title":"Alternative fuzzy controller logics","authors":"B. Schott, T. Whalen","doi":"10.1109/FUZZY.1994.343929","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343929","url":null,"abstract":"We compare six fuzzy logics used to control a simulated inverted pendulum \"plant\". Among the six is the standard \"Mamdani\" fuzzy logic. All systems contain eleven rules and are optimized for fuel economy. Mamdani's logic fares very well in the comparisons, but serious challengers are identified.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125640940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
From interval probability theory to computable fuzzy first-order logic and beyond 从区间概率论到可计算模糊一阶逻辑及以后
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343608
D. Buehrer
{"title":"From interval probability theory to computable fuzzy first-order logic and beyond","authors":"D. Buehrer","doi":"10.1109/FUZZY.1994.343608","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343608","url":null,"abstract":"This paper first presents a simple explanation for the min/max bounds which are used in interval probability theory (IPT), possibility theory, fuzzy rough sets, and vague logic. Based on this definition, a computable version of first-order fuzzy logic is defined, where all of the upper bounds for instances of a theorem and its negation are guaranteed to eventually be listed. Based on this fuzzy logic, a complete version of fuzzy Prolog is defined. This fuzzy Prolog is then used to give some examples of fuzzy Prolog definitions of fuzzy concepts such as fuzzy linguistic variables, fuzzy modifiers, fuzzy quantifiers, and various kinds of fuzzy norms and conorms.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121656734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
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