Advanced Fuzzy Systems Design and Applications
By: by Yaochu Jin
Series: Studies in Fuzziness and Soft Computing -- 112; Studies in Fuzziness and Soft Computing -- 112
Publisher: Physica-Verlag HD; Imprint: Physica
Published: 2003
Place of publication: Heidelberg
Language: eng
Format: [electronic resource] /
Number of pages: 271
ISBN-13: 9783790825206; 9783790817713
Subjects: Data structures (Computer science); Computer science; Artificial intelligence; Computer software
Description: This book presents a variety of recently developed methods for generating fuzzy rules from data with the help of neural networks and evolutionary algorithms. Special efforts have been put on dealing with knowledge incorporation into neural and evolutionary systems and knowledge extraction from data with the help of fuzzy logic. On the one hand, knowledge that is understandable to human beings can be extracted from data using evolutionary and learning methods by maintaining the interpretability of the generated fuzzy rules. On the other hand, a priori knowledge like expert knowledge and human preferences can be incorporated into evolution and learning, taking advantage of the knowledge representation capability of fuzzy rule systems and fuzzy preference models. Several engineering application examples in the fields of intelligent vehicle systems, process modeling and control and robotics are presented.
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Table of contents: title: Fuzzy Sets and Fuzzy Systems; title: Evolutionary Algorithms; title: Artificial Neural Networks; title: Conventional Data-driven Fuzzy Systems Design; title: Neural Network Based Fuzzy Systems Design; title: Evolutionary Design of Fuzzy Systems; title: Knowledge Discovery by Extracting Interpretable Fuzzy Rules; title: Fuzzy Knowledge Incorporation into Neural Networks; title: Fuzzy Preferences Incorporation into Evolutionary Multi-objective Optimization.