Modeling Uncertainty with Fuzzy Logic

1. Front Matter

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2. Introduction

   • Asli Celikyilmaz, I. Burhan Türksen

   Pages 1-10

3. Fuzzy Sets and Systems

   • Asli Celikyilmaz, I. Burhan Türksen

   Pages 11-50

4. Improved Fuzzy Clustering

   • Asli Celikyilmaz, I. Burhan Türksen

   Pages 51-104

5. Fuzzy Functions Approach

   • Asli Celikyilmaz, I. Burhan Türksen

   Pages 105-147

6. Modeling Uncertainty with Improved Fuzzy Functions

   • Asli Celikyilmaz, I. Burhan Türksen

   Pages 149-215

7. Experiments

   • Asli Celikyilmaz, I. Burhan Türksen

   Pages 217-304

8. Conclusions and Future Work

   • Asli Celikyilmaz, I. Burhan Türksen

   Pages 305-311

9. Back Matter

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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 stock? 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.

• Fuzziness
• Fuzzy Functions
• Fuzzy Logic
• Modelling Uncertainty
• Type-2 Fuzzy Functions
• fuzzy sets
• fuzzy system
• knowledge
• model
• modeling

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)

• BISC - The Berkeley Initiative in Soft Computing Electrical Eng. and Computer Sciences Department, University of California, Berkeley, Berkeley, USA

  Asli Celikyilmaz

• Mechanical & Industrial Engineering, University of Toronto , Toronto, Canada

  I. Burhan Türksen

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