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[1992 Proceedings] IEEE International Conference on Fuzzy Systems最新文献

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Efficient detection of potential inconsistency in taxonomic knowledge with uncertainty 具有不确定性的分类知识中潜在不一致性的有效检测
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258707
H.L. Larsen, R. Yager
{"title":"Efficient detection of potential inconsistency in taxonomic knowledge with uncertainty","authors":"H.L. Larsen, R. Yager","doi":"10.1109/FUZZY.1992.258707","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258707","url":null,"abstract":"The authors present the logical framework for detection of potential conflicts in knowledge bases with uncertainty. In the solution, it is assumed that the uncertainty measure is modeled by the possibilistic necessity measure. The method presented allows the modeling of the effect of a user defined certainty threshold for belief propagation, and utilization of a partially inconsistent knowledge base. An efficient computation method is presented which is applicable for knowledge in a certain simple form, typically satisfied by a taxonomic knowledge base. The deductive system implemented by this method deals properly with cycles, and is both sound and complete.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130651551","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: 0
Pattern classification by distributed representation of fuzzy rules 基于模糊规则分布式表示的模式分类
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258736
H. Ishibuchi, K. Nozaki, H. Tanaka
{"title":"Pattern classification by distributed representation of fuzzy rules","authors":"H. Ishibuchi, K. Nozaki, H. Tanaka","doi":"10.1109/FUZZY.1992.258736","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258736","url":null,"abstract":"The authors introduce the concept of distributed representation of fuzzy rules and apply it to classification problems. Distributed representation is implemented by superimposing many fuzzy rules corresponding to different fuzzy partitions of a pattern space. This means that many fuzzy rule tables are simultaneously employed, corresponding to different fuzzy partitions in fuzzy inference. To apply distributed representation of fuzzy rules to pattern classification problems, the authors first propose an algorithm to generate fuzzy rules from numerical data. Next they propose a fuzzy inference method using the generated fuzzy rules. The classification power of distributed representation was compared with that of ordinary fuzzy rules which can be viewed as a local representation.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126886353","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: 40
Minimization of combined sewer overflows using fuzzy logic control 用模糊逻辑控制最小化合流污水溢流
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258649
S.-L. Hou, N. L. Ricker
{"title":"Minimization of combined sewer overflows using fuzzy logic control","authors":"S.-L. Hou, N. L. Ricker","doi":"10.1109/FUZZY.1992.258649","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258649","url":null,"abstract":"The use of fuzzy logic control in minimizing the combined sewer overflows (CSOs) for a small but representative section of the Seattle Metro collection system is discussed. Combined sewers carry both sanitary sewage and storm runoff. The problem considered is the real-time control of the CSOs, which consist of about 160 km of interconnected pipes ranging from 0.3 m to 3.6 m in diameter. A fuzzy logic controller has been designed for a three-reservoir subsystem representing the most common connection in the combined sewer systems. This application of fuzzy logic control on the three-reservoir system suggests that ii is quite promising for online control and minimization of CSOs.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126322723","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: 4
Approaches to the handling of fuzzy input data in neural networks 神经网络中模糊输入数据的处理方法
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258601
M. E. Cohen, D. Hudson
{"title":"Approaches to the handling of fuzzy input data in neural networks","authors":"M. E. Cohen, D. Hudson","doi":"10.1109/FUZZY.1992.258601","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258601","url":null,"abstract":"Neural networks in general lend themselves well to dealing with uncertainty, in that weights are adjusted according to input data. A number of issues arise in neural network research in the handling of uncertain or fuzzy information. These can be divided into several areas: input data; propagation of results through the network: and interpretation of final results. In terms of the fuzzy implementation of neural networks each area is discussed in turn, with possible approaches summarized for each. The introduction of fuzzy input causes substantial problems in most neural network learning algorithms. The learning algorithm must be able to handle interval data. A number of approaches to this problem are outlined. These fall into two main categories: (1) introduction of a preprocessor of some sort in order to handle the fuzzy input; and (2) direct modification of the learning algorithm to handle interval data.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115889399","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
Design of a fuzzy controller with normalization circuits 带归一化电路的模糊控制器设计
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258686
O. Izhizuka, K. Tanno, Z. Tang, H. Matsumoto
{"title":"Design of a fuzzy controller with normalization circuits","authors":"O. Izhizuka, K. Tanno, Z. Tang, H. Matsumoto","doi":"10.1109/FUZZY.1992.258686","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258686","url":null,"abstract":"Novel fuzzy logic circuits for composing a fuzzy controller based on fuzzy inference are presented. The circuits consist of membership function circuits. MIN operation circuits, and normalization circuits using current-mode bipolar transistors. Normalization circuits are used as a defuzzifier without dividers. Simulation results demonstrating the functionality of the circuits are reported. The results show the normal and high-speed operation of the circuits.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115450244","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
Compacting rules for fuzzy production system computation 模糊生产系统计算的压缩规则
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258782
A. Bugariin, S. Barro, R. Ruíz
{"title":"Compacting rules for fuzzy production system computation","authors":"A. Bugariin, S. Barro, R. Ruíz","doi":"10.1109/FUZZY.1992.258782","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258782","url":null,"abstract":"The authors analyze the inference process in fuzzy production systems which have linked rules. The process for obtaining inferences in fuzzy production systems described by a base of linked fuzzy conditional statements is characterized by a very high number of operations to be performed. During the development of the process, an important simplification may be achieved by means of a partial compaction of the rule base into punctual values. The values summarize the relationship between the linguistic values associated with the variables, which establish links between fuzzy conditional statements. As a consequence, an important reduction in the computation time and in the storage memory requirements can be achieved.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115530986","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: 14
Fuzzy control of backpropagation 反向传播的模糊控制
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258787
P. Arabshahi, J.J. Choi, R. Marks, T. P. Caudell
{"title":"Fuzzy control of backpropagation","authors":"P. Arabshahi, J.J. Choi, R. Marks, T. P. Caudell","doi":"10.1109/FUZZY.1992.258787","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258787","url":null,"abstract":"The authors propose a fuzzy logic controlled implementation of the backpropagation training algorithm for layered perceptrons. The heuristics for adjusting the value of the learning rate eta are incorporated into a simple fuzzy control system. This provides automatic tuning of the learning rate parameter depending on the shape of the error surface. The application of this straightforward procedure was shown to be able to dramatically improve training time in some problems.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129794957","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: 45
Modeling and experiments in fuzzy control 模糊控制的建模与实验
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258747
K. Wu, S. Outangoun, S. Nair
{"title":"Modeling and experiments in fuzzy control","authors":"K. Wu, S. Outangoun, S. Nair","doi":"10.1109/FUZZY.1992.258747","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258747","url":null,"abstract":"Fuzzy logic controllers can be programmed with minimal knowledge about the system dynamics and are capable of tuning their structure starting with simple rules. This capability was experimentally demonstrated for DC motor controlled mechanical systems using two load cases. In each case, the controller was initialized with rudimentary rules and experimentally tuned online using gradient descent techniques. Such control strategies provide a convenient framework to incorporate human experience and expert knowledge. A self-organizing tuning algorithm is proposed for fuzzy controllers to compensate for imprecision in modelling and for system nonlinearities.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125309736","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: 9
Fuzzy rule based approach for robot motion control 基于模糊规则的机器人运动控制方法
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258693
G. Raju, J. Zhou
{"title":"Fuzzy rule based approach for robot motion control","authors":"G. Raju, J. Zhou","doi":"10.1109/FUZZY.1992.258693","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258693","url":null,"abstract":"A fuzzy rule based approach for robot motion control is proposed to eliminate the computational complexity of the inverse kinematics problem associated with the conventional mathematical algorithm. Based upon the study of forward kinematics, a strategy for formulating the fuzzy rule set is proposed. A hierarchy is used in structuring the rules to reduce the number of rules needed for a complete fuzzy rule set. Simulations have shown that, by consulting the fuzzy rule sets, a robot can follow the user specified trajectory within the specified error limit.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127611644","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
Fuzzy semantics and fuzzy constraint networks 模糊语义与模糊约束网络
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258793
J. Bowen, R. Lai, D. Bahler
{"title":"Fuzzy semantics and fuzzy constraint networks","authors":"J. Bowen, R. Lai, D. Bahler","doi":"10.1109/FUZZY.1992.258793","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258793","url":null,"abstract":"After reviewing the notion of crisp constraint networks and their relationship to semantics in classical logic, the authors define fuzzy constraint networks and their relationship to fuzzy logic. Then they introduce Khayyam, a fuzzy constrained-based programming language which implements much of Zadeh's PRUF formalism. In Khayyam, any sentence in the first-order fuzzy predicate calculus is a well-formed constrained statement. Finally, using Khayyam to address an equipment selection application, the expressive power of constraint-based languages is illustrated.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128313870","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: 35
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