Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society最新文献

Analysing uncertain data in decision support systems 决策支持系统中的不确定数据分析

Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-09-17 DOI: 10.1109/ISUMA.1995.527735

K. Schill

引用次数: 4

On estimation of temporal fuzzy sets for signal analysis: FCM vs. FMLE approaches 信号分析中时间模糊集的估计:FCM与FMLE方法

Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-09-17 DOI: 10.1109/ISUMA.1995.527760

B. Kosanovic, L. Chaparro, R. Sclabassi

引用次数: 4

Ordering fuzzy sets generated by a neural network algorithm 用神经网络算法生成排序模糊集

Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-09-17 DOI: 10.1109/ISUMA.1995.527799

L. Sztandera

{"title":"Ordering fuzzy sets generated by a neural network algorithm","authors":"L. Sztandera","doi":"10.1109/ISUMA.1995.527799","DOIUrl":"https://doi.org/10.1109/ISUMA.1995.527799","url":null,"abstract":"Ordering fuzzy subsets is an important event in dealing with fuzzy decision problems in many areas. This issue has been of concern for many researchers over the years. Also, in the last several years, there has been a large and energetic upswing in neuroengineering research aimed at synthesizing fuzzy logic with computational neural networks. The two technologies often complement each other: neural networks supply the brute force necessary to accommodate and interpret large amounts of sensor data and fuzzy logic provides a structural framework that utilizes and exploits these low-level results. As a neural network is well known for its ability to represent functions, and the basis of every fuzzy model is the membership function, so the natural application of neural networks in fuzzy models has emerged to provide good approximations to the membership functions that are essential to the success of the fuzzy approach. This paper evaluates and analyzes the performance of available methods of ranking fuzzy subsets on a set of selected examples that cover possible situations we might encounter as defining fuzzy subsets at each node of a neural network. Through this analysis, suggestions as to which methods have better performance for utilization in neural network architectures, as well as criteria for choosing an appropriate method for ranking are made.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131902252","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: 2

Weighted fuzzy mean filters for heavy-tailed noise removal 重尾噪声去除的加权模糊均值滤波器

Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-09-17 DOI: 10.1109/ISUMA.1995.527763

Chang-Shing Lee, Y. Kuo, Pao-Ta Yu

引用次数: 19

An interval fuzzy truth-value approach to the generalized modus ponens 广义模式的区间模糊真值法

Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527797

J. Yen, B. Lee

引用次数: 0

Seismic response control tests of building structure by fuzzy optimal logic 基于模糊优化逻辑的建筑结构地震反应控制试验

Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527667

H. Fujitani, M. Iiba, Y. Kitagawa, M. Midorikawa, T. Miyoshi, H. Kawamura, A. Tani, T. Mochio

引用次数: 2

Genetic algorithm based redundancy resolution of robot manipulators 基于遗传算法的机器人机械手冗余度求解

Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527715

K. K. Aydin, E. Kocaoglan

引用次数: 3

Neural network analysis of structural damage due to corrosion 结构腐蚀损伤的神经网络分析

Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527678

H. Furuta, T. Deguchi, M. Kushida

引用次数: 12

Hybrid arithmetic 混合算法

Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527766

S. Ferson, L. Ginzburg

引用次数: 21

Default reasoning with qualified syllogisms 默认推理与限定三段论

Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527728

Daniel G. Schwartz

{"title":"Default reasoning with qualified syllogisms","authors":"Daniel G. Schwartz","doi":"10.1109/ISUMA.1995.527728","DOIUrl":"https://doi.org/10.1109/ISUMA.1995.527728","url":null,"abstract":"Prior works by the author have introduced the system QUAL (herein Q) of qualified syllogisms. An example of such a syllogism is \"Most birds can fly; Tweety is a bird; therefore, it is likely that Tweety can fly.\" Q provides a formal language for expressing such syllogisms, together with a semantics which validates them. Also introduced in the prior works is the notion of a path logic. Reformulating Q as a path logic allows for the expression of modifier combination rules, such as \"From likely P and unlikely P, infer uncertain P.\" The present work builds on this, showing how to incorporate Q into a system for default reasoning. Here is introduced the notion of a dynamic reasoning system (DRS), consisting of a path logic, together with a semantic net, or more exactly, a taxonomic hierarchy that allows for multiple inheritance. The taxonomic hierarchy enables definition of a specificity relation, which can then be used in default reasoning (more specific information takes priority over less specific). Modifier combination rules prescribe what to do when defaults are applied in the context of multiple inheritance. Propositions derived in this manner all bear qualitative likelihood modifiers, representing the extent to which the proposition is believed.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115217492","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: 2