| Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control 2010 Edition Contributor(s): Castillo, Oscar (Editor), Pedrycz, Witold (Editor) |
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ISBN: 3642045138 ISBN-13: 9783642045134 Publisher: Springer OUR PRICE: $161.49 Product Type: Hardcover - Other Formats Published: October 2009 |
| Additional Information |
| BISAC Categories: - Mathematics | Applied - Computers | Intelligence (ai) & Semantics - Technology & Engineering | Engineering (general) |
| Dewey: 006.3 |
| LCCN: 2009937149 |
| Series: Studies in Computational Intelligence |
| Physical Information: 0.81" H x 6.14" W x 9.21" (1.45 lbs) 327 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: We describe in this book, new methods for evolutionary design of intelligent s- tems using soft computing and their applications in modeling, simulation and c- trol. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in four main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of evolutionary design of fuzzy systems in intelligent control, which consists of papers that propose new methods for designing and optimizing intelligent controllers for different applications. The second part c- tains papers with the main theme of evolutionary design of intelligent systems for pattern recognition applications, which are basically papers using evolutionary al- rithms for optimizing modular neural networks with fuzzy systems for response - tegration, for achieving pattern recognition in different applications. The third part contains papers with the themes of models for learning and social simulation, which are papers that apply intelligent systems to the problems of designing learning - jects and social agents. The fourth part contains papers that deal with intelligent s- tems in robotics applications and hardware implementations. In the part of Intelligent Control there are 5 papers that describe different c- tributions on evolutionary optimization of fuzzy systems in intelligent control. The first paper, by Ricardo Martinez-Marroquin et al. |