Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering

Covering the latest issues and achievements, this well documented, precisely presented text is timely and suitable for graduate and upper undergraduate students in knowledge engineering, intelligent systems, AI, neural networks, fuzzy systems, and related areas. The author's goal is to explain the principles of neural networks and fuzzy systems and to demonstrate how they can be applied to building knowledge-based systems for problem solving. Especially useful are the comparisons between different techniques (AI rule-based methods, fuzzy methods, connectionist methods, hybrid systems) used to solve the same or similar problems.

Anca Ralescu, Associate Professor of Computer Science, University of Cincinnati

Dr. Kasabov uses recent findings and insights to lay bare the foundations of neural networks, fuzzy systems and knowledge engineering. His practical approach guides the reader through a series of challenging problems, and his writing is clear and understandable. This text will be an asset to the knowledge-engineering community.

H. Jaap van den Herik, University of Limburg, Maastricht, The Netherlands

This is an excellent undergraduate/junior graduate text on three of the current topics in AI: expert systems, neural networks, and fuzzy logic. The theme of the book is the appropriate use of symbolic and connectionists AI techniques, including judicious combinations of these techniques, in problem solving. A strong feature of the book is that it is replete with applications in engineering, business, and finance. This together with its accessible style should make it attractive to a broad readership.

Duc Truong Pham, Professor and Director of the Intelligent Systems Laboratory, School of Engineering, University of Wales Cardiff, United Kingdom