Hirohide Ushida, Tomohiko Sato (auth.), Takeshi Furuhashi (eds.)3540606076, 9783540606079
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.
Table of contents :
Fuzzy associative memory system and its application to multi-modal interface….Pages 1-18
Hybrid connectionist fuzzy systems for speech recognition and the use of connectionist production systems….Pages 19-33
Fuzzy gaussian potential neural networks using a functional reasoning….Pages 34-47
Recurrent fuzzy logic using neural network….Pages 48-55
Information aggregating networks based on extended Sugeno’s fuzzy integral….Pages 56-66
A neuro-fuzzy architecture for high performance classification….Pages 67-84
Investigation of stability and robustness of a fuzzy traction control system….Pages 85-100
Knowledge-based rules for control of the sake (Ginjoshu) making process and their application in fuzzy control….Pages 101-110
A framework for studying the effects of dynamic crossover, mutation, and population sizing in genetic algorithms….Pages 111-126
Unsupervised/supervised learning for RBF-fuzzy system….Pages 127-147
Genetic algorithms for the development of fuzzy controllers for mobile robots….Pages 148-172
A new approach to genetic based machine learning and an efficient finding of fuzzy rules….Pages 173-189
A neuro-money recognition using optimized masks by GA….Pages 190-201
Genetic-fuzzy systems for financial decision making….Pages 202-223
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