This clearly-structured, classroom-tested textbook/reference presents a methodical introduction to the field of CI. Providing an authoritative insight into all that is necessary for the successful application of CI methods, the book describes fundamental concepts and their practical implementations, and explains the theoretical background underpinning proposed solutions to common problems. Only a basic knowledge of mathematics is required. Features: provides electronic supplementary material at an associated website, including module descriptions, lecture slides, exercises with solutions, and software tools; contains numerous examples and definitions throughout the text; presents self-contained discussions on artificial neural networks, evolutionary algorithms, fuzzy systems and Bayesian networks; covers the latest approaches, including ant colony optimization and probabilistic graphical models; written by a team of highly-regarded experts in CI, with extensive experience in both academia and industry.
The main focus of this text is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary ...
This enhanced second edition to the definitive textbook on Computational Intelligence has been fully revised and expanded with new content on swarm intelligence, deep learning, fuzzy data analysis, and discrete decision graphs.
Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, ...
This book integrates various natural and engineering disciplines to establish Computational Intelligence. This is the first comprehensive textbook on the subject, supported with lots of practical examples.
This book presents new research into using advanced artificial intelligence techniques to guide software quality improvements.
Summary of the fundamental concepts with solved examples is a unique combination and highlight of this book. This book presents a summary of artificial intelligence and machine learning techniques in its first two chapters.
This book focuses on computational intelligence techniques and their applications -- fast-growing and promising research topics that have drawn a great deal of attention from researchers over the years.
Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence.
1996 Biennial Conference of the North American Fuzzy Information Processing Society, NAFIPS, 19–22 June 1996, 221 –224. Lindell, Y. and Pinkas, B. (2000). Privacy preserving data mining. In: Lecture Notes in Computer Science, vol.
The book covers the main approaches used in computational intelligence, including fuzzy logic, neural networks, evolutionary computation, learning theory, and probabilistic methods, all of which can be collectively viewed as soft computing.