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Modeling Uncertainty with Fuzzy Logic: With Recent Theory and Applications (Studies in Fuzziness and Soft Computing)
 
 
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Modeling Uncertainty with Fuzzy Logic: With Recent Theory and Applications (Studies in Fuzziness and Soft Computing) [Hardcover]

Asli Celikyilmaz (Author), I. Burhan Türksen (Author)

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Book Description

3540899235 978-3540899235 April 14, 2009 1

The objective of this book is to present an uncertainty modeling approach using a new type of fuzzy system model via "Fuzzy Functions". Since most researchers on fuzzy systems are more familiar with the standard fuzzy rule bases and their inference system structures, many standard tools of fuzzy system modeling approaches are reviewed to demonstrate the novelty of the structurally different fuzzy functions, before we introduced the new methodologies. To make the discussions more accessible, no special fuzzy logic and system modeling knowledge is assumed. Therefore, the book itself may be a reference for some related methodologies to most researchers on fuzzy systems analyses. For those readers, who have knowledge of essential fuzzy theories, Chapter 1, 2 should be treated as a review material. Advanced readers ought to be able to read chapters 3, 4 and 5 directly, where proposed methods are presented. Chapter 6 demonstrates experiments conducted on various datasets.


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Editorial Reviews

Review

From the reviews: “The present book has as goal the representation and utilization of uncertainty by means of fuzzy functions. … The book begins with a very good overview of the basic notions and principles related to fuzzy sets and systems … . The fuzzy models proposed in this book can be used with success by researchers from various domains of activity: engineering, economics, biology, sociology etc., in order to model complex systems.” (Ion Iancu, Zentralblatt MATH, Vol. 1168, 2009)

From the Back Cover

The objective of this book is to present an uncertainty modeling approach using a new type of fuzzy system model via "Fuzzy Functions". Since most researchers on fuzzy systems are more familiar with the standard fuzzy rule bases and their inference system structures, many standard tools of fuzzy system modeling approaches are reviewed to demonstrate the novelty of the structurally different fuzzy functions, before we introduced the new methodologies. To make the discussions more accessible, no special fuzzy logic and system modeling knowledge is assumed. Therefore, the book itself may be a reference for some related methodologies to most researchers on fuzzy systems analyses. For those readers, who have knowledge of essential fuzzy theories, Chapter 1, 2 should be treated as a review material. Advanced readers ought to be able to read chapters 3, 4 and 5 directly, where proposed methods are presented. Chapter 6 demonstrates experiments conducted on various datasets.

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