Computational Intelligence Paradigms: Theory & Applications using MATLAB

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CRC Press, Jan 5, 2010 - Computers - 851 pages
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Offering a wide range of programming examples implemented in MATLABŪ, Computational Intelligence Paradigms: Theory and Applications Using MATLABŪ 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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Contents

Computational Intelligence
1
Artificial Neural Networks with MATLAB
29
Artificial Neural Networks Architectures and Algorithms
69
Classification and Association Neural Networks
109
MATLAB Programs to Implement Neural Networks
165
MATLABBased Fuzzy Systems
203
Fuzzy Inference and Expert Systems
261
MATLAB Illustrations on Fuzzy Systems
307
MATLABBased Genetic Algorithm
547
Genetic Programming
591
MATLABBased Swarm Intelligence
649
Glossary of Terms
693
List of Abbreviations
737
MATLAB Toolboxes Based on CI
741
Emerging Software Packages
763
Research Projects
781

NeuroFuzzy Modeling Using MATLAB
351
NeuroFuzzy Modeling Using MATLAB
395
Evolutionary Computation Paradigms
419
Evolutionary Algorithms Implemented Using MATLAB
491
References
787
Index
821
Untitled
828
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About the author (2010)

S. Sumathi is an assistant professor in the Department of Electrical and Electronics Engineering at PSG College of Technology, Coimbatore, India. Her research interests include neural networks, fuzzy systems, genetic algorithms, pattern recognition and classification, data warehousing and mining, operating systems, and parallel computing.

Surekha Paneerselvam is a lecturer in the Department of Electronics and Communication Engineering at Adhiyamaan College of Engineering, Hosur, India. Her research interests include robotics, virtual instrumentation, mobile communication, and computational intelligence.

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