Konar A. Computational Intellingence. Principles, Techniques and Applications

Springer, 2005, -713 p.The book takes a modest attempt to cover the entire framework of computational intelligence and its applications in a single volume. It includes 23 chapters, covering all aspects of the subject in a clear, precise and highly comprehensive style. The book also includes two appendices. Appendix-A contains sample runs of programs, the source codes of which are supplied in a companion CD. Appendix-B includes evolutionary algorithms of recent interest, which are increasingly being used to handle complex engineering problems of diverse domains.
This is the first text on the subject that covers all aspects of computational intelligence in a clear, precise and highly comprehensive style.
The book includes plenty of numerical examples and worked out problems.
The exercise is carefully organized to guide students to handle complex real world problems. Hints are given to most problems so as to enable the students to complete the solutions on their own.
Case studies on control, databases, telecommunication, image understanding and robotics will help the students to grow interest in the subject and enhance their potential to handle problems of similar domains.
Research problems included in chapter 23 will enable graduate researchers to identify problems of their own choice.
Source code of some interesting problems supplied in the companion CD will enhance the level of confidence of the students as they can examine the direct impact of the theories in practical problems.An Introduction to Computational Intelligence
Fuzzy Sets and Relations
Fuzzy Logic and Approximate Reasoning
Fuzzy Logic in Process Control
Fuzzy Pattern Recognition
Fuzzy Databases and Possibilistic Reasoning
Introduction to Machine Learning Using Neural Nets
Supervised Neural Learning Algorithms
Unsupervised Neural Learning Algorithms
Competitive Learning Using Neural Nets
Neuro-dynamic Programming by Reinforcement
Evolutionary Computing Algorithms
Belief Calculus and Probabilistic Reasoning
Reasoning in Expert Systems Using Fuzzy Petri Nets
Image Matching Using Fuzzy Moment Descriptors
Behavioral Synergism of Soft Computing Tools
Object Recognition from Gray Images Using Fuzzy ADALINE Neurons
Distributed Machine Learning Using Fuzzy Cognitive Maps
Machine Learning Using Fuzzy Petri Nets
Computational Intelligence in Telecommunication Networks
Computational Intelligence in Mobile Robotics
Emerging Areas of Computational Intelligence
Research Problems for Graduate Thesis and Pre-Ph D Preparatory Courses
A: Sample Run of Programs Included in the CD
B: Evolutionary Algorithms of Current Interest