Sumathi S., Surekha P. Computational Intelligence Paradigms. Theory & Applications using MatLAB

CRC Press, 2010, -835 p.Computational intelligence is a well-established paradigm, where new theories with a sound biological understanding have been evolving. Defining computational intelligence is not an easy task. In a nutshell, which becomes quite apparent in light of the current research pursuits, the area is heterogeneous with a combination of such technologies as neural networks, fuzzy systems, rough set, evolutionary computation, swarm intelligence, probabilistic reasoning, multi-agent systems, etc. Just like people, neural networks learn from experience, not from programming.
Neural networks are good at pattern recognition, generalization, and trend prediction. They are fast, tolerant of imperfect data, and do not need formulas or rules. Fuzzy logic in the narrow sense is a promising new chapter of formal logic whose basic ideas were formulated by Lotfi Zadeh. The aim of this theory is to formalize the approximate reasoning we use in everyday life, the object of investigation being the human aptitude to manage vague properties. This work is intended to help, provide basic information, and serve as a first step for individuals who are stranded in the mind-boggling universe of evolutionary computation (EC). Over the past years, global optimization algorithms imitating certain principles of nature have proved their usefulness in various domains of applications.
The aim of this book is to furnish some theoretical concepts and to sketch a general framework for computational intelligence paradigms such as artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms, genetic programming, and swarm intelligence. The book includes a large number of intelligent computing methodologies and algorithms employed in computational intelligence research. The book also offers a set of solved programming examples related to computational intelligence paradigms using MatLAB software. Additionally, such examples can be repeated under the same conditions, using different data sets. Researchers, academicians, and students in computational intelligence can use this book to verify their ideas related to evolution dynamics, self-organization, natural and artificial morphogenesis, emergent collective behaviors, swarm intelligence, evolutionary strategies, genetic programming, and evolution of social behaviors.Computational Intelligence
Artificial Neural Networks with MatLAB
Artificial Neural Networks - Architectures and Algorithms
Classification and Association Neural Networks
MatLAB Programs to Implement Neural Networks
MatLAB-Based Fuzzy Systems
Fuzzy Inference and Expert Systems
MatLAB Illustrations on Fuzzy Systems
Neuro-Fuzzy Modeling Using MatLAB
Neuro-Fuzzy Modeling Using MatLAB
Evolutionary Computation Paradigms
Evolutionary Algorithms Implemented Using MatLAB
MatLAB-Based Genetic Algorithm
Genetic Programming
MatLAB-Based Swarm Intelligence
A: Glossary of Terms
B: List of Abbreviations
C: MatLAB Toolboxes Based on CI
D: Emerging Software Packages
E: Research Projects