Advances in Fuzzy Logic, Neural Networks and Genetic Algorithms : IEEE/Nagoya-University World Wisepersons Workshop, Nagoya, Japan, August 9 - 10, 1994. Selected Papers. 1st ed. 1995

種類:

電子ブック

責任表示:

edited by Takeshi Furuhashi

出版情報:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1995

著者名:

• Furuhashi, Takeshi.
• SpringerLink (Online service)

シリーズ名:

Lecture Notes in Artificial Intelligence ; 1011

ISBN:

9783540484578 [3540484574]    

注記:

Fuzzy associative memory system and its application to multi-modal interface -- Hybrid connectionist fuzzy systems for speech recognition and the use of connectionist production systems -- Fuzzy gaussian potential neural networks using a functional reasoning -- Recurrent fuzzy logic using neural network -- Information aggregating networks based on extended Sugeno's fuzzy integral -- A neuro-fuzzy architecture for high performance classification -- Investigation of stability and robustness of a fuzzy traction control system -- Knowledge-based rules for control of the sake (Ginjoshu) making process and their application in fuzzy control -- A framework for studying the effects of dynamic crossover, mutation, and population sizing in genetic algorithms -- Unsupervised/supervised learning for RBF-fuzzy system -- Genetic algorithms for the development of fuzzy controllers for mobile robots -- A new approach to genetic based machine learning and an efficient finding of fuzzy rules -- A neuro-money recognition using
This book presents 14 rigorously reviewed revised papers selected from more than 50 submissions for the 1994 IEEE/ Nagoya-University World Wisepersons Workshop, WWW'94, held in August 1994 in Nagoya, Japan. The combination of approaches based on fuzzy logic, neural networks and genetic algorithms are expected to open a new paradigm of machine learning for the realization of human-like information processing systems. The first six papers in this volume are devoted to the combination of fuzzy logic and neural networks; four papers are on how to combine fuzzy logic and genetic algorithms. Four papers investigate challenging applications of fuzzy systems and of fuzzy-genetic algorithms.

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