Soft Computing

1 Evolutionary Algorithms.- 2 Artificial Neural Networks.- 3 Fuzzy Systems.- 4 Evolutionary Design of Artificial Neural Networks.- 5 Evolutionary Design of Fuzzy Systems.- 6 Neuro-fuzzy Systems.- 7 Fuzzy Evolutionary Algorithms.- 8 Natural Parallel (Soft) Computing.- 9 Epilogue.

From the reviews:

"The authors explain that soft computing is a term covering such computing methodologies which are, in some sense, tolerant of imprecision, uncertainty and partial truth. There are three of them exposed in this book, namely: fuzzy logic, evolutionary algorithms and artificial neural networks - all inspired by nature. ... The book contains many examples of applications, which cover a broad spectrum: finance, medicine, robotics and others." (Jerzy Mycka, Zentralblatt MATH, Vol. 981, 2002)

"The reviewed book is intended both for undergraduate students in soft computing disciplines as well as for engineers, practitioners, and problem solvers in many areas of application. ... The main theme of the reviewed book is integration and synergistic co-operation of a few soft-computing methodologies that have their roots in neural systems. ... I fully agree with the authors that several techniques presented can be used sequentially to solve parts of the problem in a 'pipeline' fashion, because it ... will be used increasingly." (Dr. Ing. Miroslav Svítek, Neural Network World, Vol. 12 (2), 2002)

"The book Soft Computing: Integrating Evolutionary, Neural and Fuzzy Systems provides a comprehensive introduction to the area of soft computing addressing three of the main constituents of this discipline: fuzzy logic, neural computing and evolutionary computing. ... The book is primarily aimed at undergraduate students and practitioners in the field. The book is organized in a modular form which enable readers to select their own pathway through the chapters. ... The academic content is well supported by informative practical examples and case studies." (Liam Maguire, Artificial Intelligence Review, Vol. 23, 2006)