book announcemet

From: Plamen Angelov (P.P.Angelov@lboro.ac.uk)
Date: Wed Dec 19 2001 - 16:12:27 MET

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    A new book is to be published in January by Springer, Physica-Verlag,

    Angelov, P.P., Evolving Rule-Based Models: A Tool for Design of Flexible
    Adaptive Systems'
    (http://www.springer.de/cgi-bin/search_book.pl?isbn=3-7908-1457-1)

    2002. XIV, 213 pp. 106 figs., 9 tabs. Hardcover 3-7908-1457-1
    Recommended Retail Price: DM 109,90
    A monograph written for: Researchers and practitioners in computational
    intelligence and engineering

    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.

    Keywords: Evolving Rule-Based Models, Flexible Adaptive Systems, Online
    Model Identification, Intelligent Control

    Contents:
    1.Introduction.
    Part I: System Modelling: Basic Principles:
    2.Conventional Methods
    3.Flexible Models.
    Part II: Flexible Models Identification:
    4. Non-linear Approach to (Off-line) Identification of Flexible Models
    5. Quasi-linear Approach to FRB Models (Off-line) Identification
    6. Intelligent and Smart Adaptive Systems
    7. On-line Identification of Flexible TSK-type Models
    Part III: Engineering Applications:
    8. Modelling Indoor Climate Control Systems
    9. On-line Modelling of Fermentation Processes
    10. Intelligent Risk Assessment
    11. Conclusions.

    The book gives both easy-to-follow introduction to System Modelling and
    Fuzzy Identification and original contributions in direct non-linear
    off-line and on-line identification of fuzzy rule-based models. Illustrated
    with a number of practical examples from air-conditioning simulation,
    biotech processes modelling and risk assessment it makes a kind of a bridge
    between 'pure' mathematically-oriented theoretical texts and the needs of
    the real engineering practice.

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