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Computational Intelligence Paradigms Theory Applications Using Matlab 1st Edition S Sumathi And Surekha Paneerselvam

  • SKU: BELL-2524572
Computational Intelligence Paradigms Theory Applications Using Matlab 1st Edition S Sumathi And Surekha Paneerselvam
$ 31.00 $ 45.00 (-31%)

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Computational Intelligence Paradigms Theory Applications Using Matlab 1st Edition S Sumathi And Surekha Paneerselvam instant download after payment.

Publisher: CRC Press
File Extension: PDF
File size: 8.75 MB
Pages: 829
Author: S. Sumathi and Surekha Paneerselvam
ISBN: 143980902X
Language: English
Year: 2010
Edition: 1

Product desciption

Computational Intelligence Paradigms Theory Applications Using Matlab 1st Edition S Sumathi And Surekha Paneerselvam by S. Sumathi And Surekha Paneerselvam 143980902X instant download after payment.

Offering a wide range of programming examples implemented in MATLAB®, Computational Intelligence Paradigms: Theory and Applications Using MATLAB® presents theoretical concepts and a general framework for computational intelligence (CI) approaches, including artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous intelligent computing methodologies and algorithms used in CI research. The book first focuses on neural networks, including common artificial neural networks; neural networks based on data classification, data association, and data conceptualization; and real-world applications of neural networks. It then discusses fuzzy sets, fuzzy rules, applications of fuzzy systems, and different types of fused neuro-fuzzy systems, before providing MATLAB illustrations of ANFIS, classification and regression trees, fuzzy c-means clustering algorithms, fuzzy ART map, and Takagi–Sugeno inference systems. The authors also describe the history, advantages, and disadvantages of evolutionary computation and include solved MATLAB programs to illustrate the implementation of evolutionary computation in various problems. After exploring the operators and parameters of genetic algorithms, they cover the steps and MATLAB routines of genetic programming. The final chapter introduces swarm intelligence and its applications, particle swarm optimization, and ant colony optimization. Full of worked examples and end-of-chapter questions, this comprehensive book explains how to use MATLAB to implement CI techniques for the solution of biological problems. It will help readers with their work on evolution dynamics, self-organization, natural and artificial morphogenesis, emergent collective behaviors, swarm intelligence, evolutionary strategies, genetic programming, and the evolution of social behaviors.

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