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Intelligent Systems: Modeling, Optimization, and Controlby Chengying Xu
Synopses & Reviews
Providing a thorough introduction to the field of soft computing techniques, Intelligent Systems: Modeling, Optimization, and Control covers every major technique in artificial intelligence in a clear and practical style. This book highlights current research and applications, addresses issues encountered in the development of applied systems, and describes a wide range of intelligent systems techniques, including neural networks, fuzzy logic, evolutionary strategy, and genetic algorithms. The book demonstrates concepts through simulation examples and practical experimental results. Case studies are also presented from each field to facilitate understanding.
The vast field of "intelligent systems" demands a high level of systematic efficiency. Intelligent Systems: Modeling, Optimization, and Control employs that same effectual style to compile all relevant system design techniques in one volume. This is that rare reference that developers can truly call a functional tool. Integrating different disciplines and data, it enables readers to draw from diverse areas to develop more efficient systems.
Table of Contents
Intelligent systems — Modeling of nonlinear systems: fuzzy logic, neural networks, and neuro-fuzzy systems — Efficient training algorithms — Fuzzy inverse model development — Model-based optimization — Neural control — Fuzzy control — Stability analysis method — Intelligent control for SISO nonlinear systems — Intelligent control for MISO nonlinear systems — Knowledge-based multivariable fuzzy control — Model-based multivariable fuzzy control.
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Computers and Internet » Artificial Intelligence » General