Modeling Uncertainty with Fuzzy Logic: With Recent Theory and Applications / Edition 1

by Asli Celikyilmaz, I. Burhan Tïrksen

Overview

The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon? Should I take an umbrella with me? Will I be able to find parking near the campus? Should I go by bus? Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future? Should I buy Chevron sk? What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed? What will be the consequences? Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, “The only satisfactory description of uncertainty is probability.

Product Details

ISBN-13:	9783642100635
Publisher:	Springer Berlin Heidelberg
Publication date:	12/15/2010
Series:	Studies in Fuzziness and Soft Computing , #240
Edition description:	Softcover reprint of hardcover 1st ed. 2009
Pages:	400
Product dimensions:	6.10(w) x 9.25(h) x 0.04(d)

Table of Contents

Fuzzy Sets and Systems.- Improved Fuzzy Clustering.- Fuzzy Functions Approach.- Modeling Uncertainty with Improved Fuzzy Functions.- Experiments.- Conclusions and Future Work.

Editorial Reviews

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 Publisher