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Evolving Rule-Based Models: A Tool for Design of Flexible Adaptive Systems / Edition 1
     

Evolving Rule-Based Models: A Tool for Design of Flexible Adaptive Systems / Edition 1

by Plamen P. Angelov
 

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ISBN-10: 3790825069

ISBN-13: 9783790825060

Pub. Date: 12/15/2010

Publisher: Physica-Verlag HD

The objects of modelling and control change due to dynamical characteristics, fault development or simply ageing. There is a need to up-date models inheriting useful structure and parameter information. The book gives an original solution to this problem with a number of examples. It treats an original approach to on-line adaptation of rule-based models and systems

Overview

The objects of modelling and control change due to dynamical characteristics, fault development or simply ageing. There is a need to up-date models inheriting useful structure and parameter information. The book gives an original solution to this problem with a number of examples. It treats an original approach to on-line adaptation of rule-based models and systems described by such models. It combines the benefits of fuzzy rule-based models suitable for the description of highly complex systems with the original recursive, non iterative technique of model evolution without necessarily using genetic algorithms, thus avoiding computational burden making possible real-time industrial applications. Potential applications range from autonomous systems, on-line fault detection and diagnosis, performance analysis to evolving (self-learning) intelligent decision support systems.

Product Details

ISBN-13:
9783790825060
Publisher:
Physica-Verlag HD
Publication date:
12/15/2010
Series:
Studies in Fuzziness and Soft Computing Series , #92
Edition description:
Softcover reprint of hardcover 1st ed. 2002
Pages:
214
Product dimensions:
6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

Introduction.- Part I: System Modelling: Basic Principles: Conventional Methods; Flexible Models.- Part II: Flexible Models Identification: Non-linear Approach to (Off-line) Identification of Flexible Models; Quasi-linear Approach to FRB Models (Off-line) Identification; Intelligent and Smart Adaptive Systems; On-line Identification of Flexible TSK-type Models.- Part III: Engineering Applications: Modelling Indoor Climate Control Systems; On-line Modelling of Fermentation Processes; Intelligent Risk Assessment; Conclusions.

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