Fuzzy Reasoning in Information, Decision and Control Systems

S.G. Tzafestas, Anastasios N. Venetsanopoulos

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English

Springer
03 October 2013

Fuzzy set theory; Automatic control engineering

Series: Intelligent Systems, Control and Automation: Science and Engineering

Summary
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Great progresses have been made in the application of fuzzy set theory and fuzzy logic. Most remarkable area of application is 'fuzzy control', where fuzzy logic was first applied to plant control systems and its use is expanding to consumer products. Most of fuzzy control systems uses fuzzy inference with max-min or max-product composition, similar to the algorithm that first used by Mamdani in 1970s. Some algorithms are developed to refine fuzzy controls systems but the main part of algorithm stays the same. Triggered by the success of fuzzy control systems, other ways of applying fuzzy set theory are also investigated. They are usually referred to as 'fuzzy expert sys tems', and their purpose are to combine the idea of fuzzy theory with AI based approach toward knowledge processing. These approaches can be more generally viewed as 'fuzzy information processing', that is to bring fuzzy idea into informa tion processing systems.

Edited by: S.G. Tzafestas, Anastasios N. Venetsanopoulos
Imprint: Springer
Edition: Softcover reprint of the original 1st ed. 1994
Volume: 11
Dimensions: Height: 235mm, Width: 155mm, Spine: 30mm
Weight: 896g
ISBN: 9789401740821
ISBN 10: 9401740828
Series: Intelligent Systems, Control and Automation: Science and Engineering
Pages: 568
Publication Date: 03 October 2013
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

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Fuzzy Reasoning in Information, Decision and Control Systems

S.G. Tzafestas, Anastasios N. Venetsanopoulos

$621.95 $497.90

Paperback

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