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Computational Intelligence: Principles, Techniques and Applications
presents both theories and applications of computational intelligence in a clear, precise and highly comprehensive style. The textbook addresses the fundamental aspects of fuzzy sets and logic, neural networks, evolutionary computing and belief networks. The application areas include fuzzy databases, fuzzy control, image understanding, expert systems, object recognition, criminal investigation, telecommunication networks, and intelligent robots. The book contains many numerical examples and homework problems with sufficient hints so that the students can solve them on their own.
Reviews / Votes
From the reviews:
Most complete book on computational intelligence.
"The book Computational Intelligence: Principles, Techniques and Applications by Dr Amit Konar provides comprehensive and excellent coverage of current topics in computational intelligence. . the book is highly suitable for use by pre-Ph.D. students, researchers, as well as practitioners in science and engineering. . The book cites numerous references at the end of each chapter." (Steve C. Chiu, International Journal of Robust and Nonlinear Control, Vol. 18, 2008)
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Target group
Primary & secondary/elementary & high school
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ISBN-13
978-3-540-27335-6 (9783540273356)
DOI
Schweitzer Classification
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.- to Machine Learning Using Neural Nets.- Supervised Neural Learning Algorithms.- Unsupervised Neural Learning Algorithms.- Competitive Learning Using Neural Nets.- Neuro-dynamic Programming by Reinforcement Learning.- Evolutionary Computing Algorithms.- Belief Calculus and Probabilistic Reasoning.- Reasoning in Expert Systems Using Fuzzy Petri Nets.- Fuzzy Models for Face Matching and Mood Detection.- 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 Tele-Communication Networks.- Computational Intelligence in Mobile Robotics.- Emerging Areas of Computational Intelligence.- Research Problems for Graduate Thesis and Pre-Ph D Preparatory Courses.
