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Evolving Rule-Based Models - new book

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Plamen P. Angelov:

Evolving Rule-Based Models - new book

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Plamen P. Angelov:
Evolving Rule-Based Models - new book

ISBN: 9783790817942

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Details of the book - Evolving Rule-Based Models


EAN (ISBN-13): 9783790817942
Publishing year: 2013
Publisher: Physica-Verlag HD

Book in our database since 2017-05-08T05:59:38+01:00 (London)
Detail page last modified on 2024-02-24T04:16:40+00:00 (London)
ISBN/EAN: 9783790817942

ISBN - alternate spelling:
978-3-7908-1794-2
Alternate spelling and related search-keywords:
Book author: angelov, bailey robert
Book title: rule, flexible design


Information from Publisher

Author: Plamen P. Angelov
Title: Studies in Fuzziness and Soft Computing; Evolving Rule-Based Models - A Tool for Design of Flexible Adaptive Systems
Publisher: Physica; Physica
214 Pages
Publishing year: 2013-03-20
Heidelberg; DE
Language: English
96,29 € (DE)
99,00 € (AT)
118,00 CHF (CH)
Available
XIII, 214 p.

EA; E107; eBook; Nonbooks, PBS / Mathematik/Grundlagen; Mathematik: Logik; Verstehen; algorithms; complex system; complex systems; decision support system; fuzzy; genetic algorithms; model; modeling; system; complexity; C; Mathematical Logic and Foundations; Systems Theory, Control; Artificial Intelligence; Applied Dynamical Systems; Engineering; Mathematische Grundlagen; Kybernetik und Systemtheorie; Künstliche Intelligenz; Mathematik für Ingenieure; BB

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.
First approach to on-line generation and adaptation of rule-based models Illustration with real engineering examples Includes supplementary material: sn.pub/extras

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