Foresight in an engineering enterprise can make the difference between success and failure, and can be vital to the effective control of industrial systems. Applying time series analysis in the on-line milieu of most industrial plants has been problematic owing to the time and computational effort required. The advent of soft computing tools offers a solution. The authors harness the power of intelligent technologies individually and in combination. Examples of the particular systems and processes susceptible to each technique are investigated, cultivating a comprehensive exposition of the improvements on offer in quality, model building and predictive control and the selection of appropriate tools from the plethora available. Application-oriented engineers in process control, manufacturing, production industry and research centres will find much to interest them in this book. It is suitable for industrial training purposes, as well as serving as valuable reference material for experimental researchers. TOC:Part I: Introduction.- Computational Intelligence: An Introduction.- Traditional Problem Definition.- Part II: Basic Intelligent Computational Technologies.- Neural Networks Approach.- Fuzzy Logic Approach.- Evolutionary Computation.- Part III: Hybrid Computational Technologies.- Neuro-fuzzy Approach.- Transparent Fuzzy/Neuro-fuzzy Modeling.- Evolving Neural and Fuzzy Systems.- Adaptive Genetic Algorithms.- Part IV: Recent Developments.- The State of the Art and Development Trends.
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