Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization

This book presents recent advances on the design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization and their application in areas such as, intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. T...

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Bibliographic Details
Other Authors: Melin, Patricia (Editor), Castillo, Oscar (Editor), Kacprzyk, Janusz (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2015, 2015
Edition:1st ed. 2015
Series:Studies in Computational Intelligence
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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245 0 0 |a Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization  |h Elektronische Ressource  |c edited by Patricia Melin, Oscar Castillo, Janusz Kacprzyk 
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260 |a Cham  |b Springer International Publishing  |c 2015, 2015 
300 |a XII, 637 p. 307 illus., 226 illus. in color  |b online resource 
505 0 |a Part I Fuzzy Logic Theory -- Part II Neural Networks Theory -- Part III Neural Networks Applications -- Part IV Nature Inspired Optimization -- Part V Nature Inspired Optimization Applications -- Part VI Optimization: Theory and Applications -- Part VII Fuzzy Logic Applications -- Part VIII Fuzzy Logic and Metaheuristic 
653 |a Optimization 
653 |a Control, Robotics, Automation 
653 |a Computational intelligence 
653 |a Artificial Intelligence 
653 |a Computational Intelligence 
653 |a Control engineering 
653 |a Artificial intelligence 
653 |a Robotics 
653 |a Automation 
653 |a Mathematical optimization 
700 1 |a Castillo, Oscar  |e [editor] 
700 1 |a Kacprzyk, Janusz  |e [editor] 
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520 |a This book presents recent advances on the design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization and their application in areas such as, intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. The book is organized in eight main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on fuzzy systems. The second part contains papers with the main theme of neural networks theory, which are basically papers dealing with new concepts and algorithms in neural networks. The third part contains papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The fourth part contains papers describing new nature-inspired optimization algorithms. The fifth part presents diverse applications of nature-inspired optimization algorithms. The sixth part contains papers describing new optimization algorithms. The seventh part contains papers describing applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. Finally, the eighth part contains papers that present enhancements to meta-heuristics based on fuzzy logic techniques