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Proceedings of 1995 IEEE International Conference on Fuzzy Systems.最新文献

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Fuzzy modelling in an intelligent data browser 智能数据浏览器中的模糊建模
Proceedings of 1995 IEEE International Conference on Fuzzy Systems. Pub Date : 1995-03-20 DOI: 10.1109/FUZZY.1995.409937
J. F. Baldwin, T. P. Martin
{"title":"Fuzzy modelling in an intelligent data browser","authors":"J. F. Baldwin, T. P. Martin","doi":"10.1109/FUZZY.1995.409937","DOIUrl":"https://doi.org/10.1109/FUZZY.1995.409937","url":null,"abstract":"The Fril fuzzy data browser is a software tool which can automatically derive rules from large bodies of data. The data need not be completely known, and the derived rules can be used to fill in missing values, highlight anomalous values, or predict values in new cases. Human expertise can be input at any stage, and hierarchical systems of rules can be generated. Rules use the fuzzy or evidential logic uncertainty calculus built-in to Fril. It is also possible to generate C-code, although rules are easier to understand, and more efficiently executed in Fril. An enhanced version of the fuzzy data browser is linked to Mathematica, giving access to sophisticated graphical and mathematical facilities. We focus on some simple examples to illustrate the use of the enhanced fuzzy data browser in developing rules which model data.<<ETX>>","PeriodicalId":150477,"journal":{"name":"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115225960","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: 12
Design of fuzzy model following servo control systems 模糊模型跟随伺服控制系统的设计
Proceedings of 1995 IEEE International Conference on Fuzzy Systems. Pub Date : 1995-03-20 DOI: 10.1109/FUZZY.1995.409920
S. Kawaji, N. Matsunaga
{"title":"Design of fuzzy model following servo control systems","authors":"S. Kawaji, N. Matsunaga","doi":"10.1109/FUZZY.1995.409920","DOIUrl":"https://doi.org/10.1109/FUZZY.1995.409920","url":null,"abstract":"In real situations, an exact dynamic model of the plants can be scarcely obtained, and the desired characteristics of the control systems are specified in wide ranges. In order to get a satisfactory solution to the problems, a new fuzzy model following servo control system is proposed in this paper. The effectiveness of the proposed method is shown for a nonlinear DC servomotor system.<<ETX>>","PeriodicalId":150477,"journal":{"name":"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114376716","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: 7
Absolute continuity of fuzzy measures 模糊测度的绝对连续性
Proceedings of 1995 IEEE International Conference on Fuzzy Systems. Pub Date : 1995-03-20 DOI: 10.1109/FUZZY.1995.409671
Zhenyuan Wang, G. Klir, Wei Wang
{"title":"Absolute continuity of fuzzy measures","authors":"Zhenyuan Wang, G. Klir, Wei Wang","doi":"10.1109/FUZZY.1995.409671","DOIUrl":"https://doi.org/10.1109/FUZZY.1995.409671","url":null,"abstract":"The purpose of this paper is to investigate the issue systematically. We identify 9 generalized types of absolute continuity which possess desirable properties, such as reflexivity and transitivity. We also study the relationship between these distinct types of absolute continuity and determine which of them are possessed by the fuzzy measure (or the lower semicontinuous fuzzy measure) defined by the fuzzy integral.<<ETX>>","PeriodicalId":150477,"journal":{"name":"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117001154","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
Fuzzy random variables revisited 重新审视模糊随机变量
Proceedings of 1995 IEEE International Conference on Fuzzy Systems. Pub Date : 1995-03-20 DOI: 10.1109/FUZZY.1995.409802
D. Ralescu
{"title":"Fuzzy random variables revisited","authors":"D. Ralescu","doi":"10.1109/FUZZY.1995.409802","DOIUrl":"https://doi.org/10.1109/FUZZY.1995.409802","url":null,"abstract":"Reviews the concept of a fuzzy random variable, its expected value, and limit theorems for sequences of fuzzy random variables. The author points out shortcomings in some concepts and results that have been defined in the literature. Finally, the author studies two inequalities involving the expected value of a fuzzy random variable: the Brunn-Minkowski inequality and the Jensen inequality. The author explores different extensions of the former, and gives an analog for the latter. Potential applications of the authors' results are to the analysis of fuzzy random variables and to statistics with inexact data.<<ETX>>","PeriodicalId":150477,"journal":{"name":"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117110983","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: 23
KF dynamic fuzzy crane system KF动态模糊起重机系统
Proceedings of 1995 IEEE International Conference on Fuzzy Systems. Pub Date : 1995-03-20 DOI: 10.1109/FUZZY.1995.410042
O. Itoh, H. Migita, J. Itoh, Y. Irie
{"title":"KF dynamic fuzzy crane system","authors":"O. Itoh, H. Migita, J. Itoh, Y. Irie","doi":"10.1109/FUZZY.1995.410042","DOIUrl":"https://doi.org/10.1109/FUZZY.1995.410042","url":null,"abstract":"Residual swing will often be generated in the overhead traveling crane drive by factors such as the delay and the friction of the machine even if it is controlled along the pattern. Therefore we have developed \"KF dynamic fuzzy crane system\" for automatic operation and put it to practical use. This system has many features as follows: cooperative control of positioning and the swing prevention by fuzzy inference; automatic crane control and fuzzy control with one programmable controller; stable operation by swing prevention at high velocities; maintenance free crane motor by using vector controlled general purpose inverter; easy automatization even on an existing crane.<<ETX>>","PeriodicalId":150477,"journal":{"name":"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123103540","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: 3
Model-based fuzzy control of a trailer type mobile robot 拖挂式移动机器人基于模型的模糊控制
Proceedings of 1995 IEEE International Conference on Fuzzy Systems. Pub Date : 1995-03-20 DOI: 10.1109/FUZZY.1995.409661
K. Tanaka
{"title":"Model-based fuzzy control of a trailer type mobile robot","authors":"K. Tanaka","doi":"10.1109/FUZZY.1995.409661","DOIUrl":"https://doi.org/10.1109/FUZZY.1995.409661","url":null,"abstract":"Tanaka and Sano (1993,1994) designed a control system for backing up a computer simulated trailer type mobile robot, which is non-linear and unstable, by applying a robust stabilization technique for fuzzy systems. Furthermore, it was shown that the designed fuzzy controller smoothly achieves backing up control of the computer simulated trailer type mobile robot from all initial positions. In this paper, the author controls a real trailer type mobile robot by applying the design method proposed in the above papers. The experimental results show that the designed fuzzy controller effectively realizes backing up control of the real trailer type mobile robot.<<ETX>>","PeriodicalId":150477,"journal":{"name":"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123610567","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
Algorithms for fuzzy inference and tuning in the fuzzy inference software FINEST 模糊推理算法及其在模糊推理软件FINEST中的调优
Proceedings of 1995 IEEE International Conference on Fuzzy Systems. Pub Date : 1995-03-20 DOI: 10.1109/FUZZY.1995.409811
T. Arnould, S. Tano, T. Miyoshi, Y. Kato, T. Oyama, A. Bastian, M. Umano
{"title":"Algorithms for fuzzy inference and tuning in the fuzzy inference software FINEST","authors":"T. Arnould, S. Tano, T. Miyoshi, Y. Kato, T. Oyama, A. Bastian, M. Umano","doi":"10.1109/FUZZY.1995.409811","DOIUrl":"https://doi.org/10.1109/FUZZY.1995.409811","url":null,"abstract":"In this paper, we explain the algorithms used in FINEST, the Fuzzy Inference Environment Software with Tuning developed at LIFE (Laboratory for International Fuzzy Engineering Research). The research themes and associated algorithms were defined to palliate the insufficiencies of usual inference methods and come naturally from the formulation of fuzzy \"if... then...\" rules. In particular, enhanced versions of combination operators, implication functions and aggregation operators are proposed, as well as a mechanism to tune the parameters used in the definition of the knowledge used in the system. Finally, one definition and formulation of backward reasoning with fuzzy \"if... then...\" rules is proposed.<<ETX>>","PeriodicalId":150477,"journal":{"name":"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121770005","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
Compatible cluster merging for fuzzy modelling 兼容聚类合并模糊建模
Proceedings of 1995 IEEE International Conference on Fuzzy Systems. Pub Date : 1995-03-20 DOI: 10.1109/FUZZY.1995.409789
U. Kaymak, R. Babuška
{"title":"Compatible cluster merging for fuzzy modelling","authors":"U. Kaymak, R. Babuška","doi":"10.1109/FUZZY.1995.409789","DOIUrl":"https://doi.org/10.1109/FUZZY.1995.409789","url":null,"abstract":"Making a fuzzy model of a dynamic process requires the tuning of many parameters. Doing this heuristically is tedious and time consuming. Clustering techniques provide an easier way for forming fuzzy model using measurements made on the system. However, the number of clusters and hence the number of rules the fuzzy rule-base must be determined a priori. It is usually not possible to determine beforehand the optimal number of rules in a rule-base. In this paper, a compatible cluster merging algorithm is suggested for finding the \"optimal\" number of rules in a rule base. It is based on the compatible cluster merging algorithm proposed recently. The original compatible cluster merging algorithm has certain undesired properties for fuzzy modelling. Hence, a modification is proposed and a modified compatible cluster merging algorithm is described. The new algorithm combines techniques from the original compatible cluster merging, fuzzy multicriteria decision making and heuristics. Examples are given that show the applicability of the proposed method.<<ETX>>","PeriodicalId":150477,"journal":{"name":"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125937438","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: 116
On the condition of adaptive neurofuzzy models 在自适应神经模糊模型的条件下
Proceedings of 1995 IEEE International Conference on Fuzzy Systems. Pub Date : 1995-03-20 DOI: 10.1109/FUZZY.1995.409755
M. Brown, P. E. An, C. Harris
{"title":"On the condition of adaptive neurofuzzy models","authors":"M. Brown, P. E. An, C. Harris","doi":"10.1109/FUZZY.1995.409755","DOIUrl":"https://doi.org/10.1109/FUZZY.1995.409755","url":null,"abstract":"Learning within fuzzy and neurofuzzy systems is becomingly increasingly important as researchers try to infer qualitative, vague information from quantitative, numeric data. The fuzzy representation of an adaptive neurofuzzy system is important both for initialisation and validation purposes, where a designer needs to interpret the knowledge stored in a network. Therefore it is important to study the convergence and rate of convergence characteristics of the parameters in a neurofuzzy model and investigate how this depends on the system's structure. This paper considers how the condition of the input fuzzy sets determines the convergence and generalisation abilities of the network and describes several new results about instantaneous least mean square training rules.<<ETX>>","PeriodicalId":150477,"journal":{"name":"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129948371","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
Fuzzy intelligent hybrid systems and their applications 模糊智能混合系统及其应用
Proceedings of 1995 IEEE International Conference on Fuzzy Systems. Pub Date : 1995-03-20 DOI: 10.1109/FUZZY.1995.409996
A. Kandel, M. Schneider
{"title":"Fuzzy intelligent hybrid systems and their applications","authors":"A. Kandel, M. Schneider","doi":"10.1109/FUZZY.1995.409996","DOIUrl":"https://doi.org/10.1109/FUZZY.1995.409996","url":null,"abstract":"This paper addresses some of the issues involved in developing a technology that supports the implementation of an autonomous fuzzy hybrid intelligent systems. The technology is based on the premise that integrated solution architectures will be much more effective and highly flexible in their ability to successfully handle a broad base of applications with a wider scope of problem variations. Hybrid systems in artificial intelligence represent a new field of research that deals with the synergism of expert systems and neural network technologies. The integration of the computational paradigms of these two highly complementary knowledge representation techniques is imperative to the process of developing effective robust intelligent systems for a large number of important applications.<<ETX>>","PeriodicalId":150477,"journal":{"name":"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130280576","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
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