Type-2 Fuzzy Logic: Theory and Applications / Edition 1

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This book describes new methods for building intelligent systems using type-2 fuzzy logic and soft computing (SC) techniques. The authors extend the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each technique offers. This book is intended to be a major reference tool and can be used as a textbook.

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Editorial Reviews

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“This research monograph offers a broad coverage of the recent developments in … type-2 fuzzy sets and fuzzy systems. … The monograph is arranged into 17 concise and well-focused chapters covering a wealth of applications and methodologies of type-2 fuzzy sets. … chapters brings some useful motivating notes and elaborates on the algorithms pertinent to the problem at hand. … a timely compendium of applications of type-2 fuzzy systems and offers the reader a sound overview of design techniques supporting the construction of such architectures.” (Witold Pedrycz, Zentralblatt MATH, Vol. 1171, 2009)

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Product Details

  • ISBN-13: 9783642095139
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 12/15/2010
  • Series: Studies in Fuzziness and Soft Computing Series, #223
  • Edition description: Softcover reprint of hardcover 1st ed. 2008
  • Edition number: 1
  • Pages: 244
  • Product dimensions: 0.55 (w) x 6.14 (h) x 9.21 (d)

Table of Contents

1 Introduction to Type-2 Fuzzy Logic.- 2 Type-1 Fuzzy Logic.- 3 Type-2 Fuzzy Logic.- 4 A Method for Type-2 Fuzzy Inference in Control Applications.- 5 Design of Intelligent Systems with Interval Type-2 Fuzzy Logic.- 6 Method for Response Integration in Modular Neural Networks with Type-2 Fuzzy Logic.- 7 Type-2 Fuzzy Logic for Improving Training Data and Response Integration in Modular Neural Networks for Image Recognition.- 8 Fuzzy Inference Systems Type-1 and Type-2 for Digital Images Edge Detection.- 9 Systematic Design of a Stable Type-2 Fuzzy Logic Controller.- 10 Experimental Study of Intelligent Controllers Under Uncertainty Using Type-1 and Type-2 Fuzzy Logic.- 11 Evolutionary Optimization of Interval Type-2 Membership Functions Using the Human Evolutionary Model.- 12 Design of Fuzzy Inference Systems with the Interval Type-2 Fuzzy Logic Toolbox.- 13 Intelligent Control of the Pendubot with Interval Type-2 Fuzzy Logic.- 14 Automated Quality Control in Sound Speakers Manufacturing Using a Hybrid Neuro-fuzzy-Fractal Approach.- 15 A New Approach for Plant Monitoring Using Type-2 Fuzzy Logic and Fractal Theory.- 16 Intelligent Control of Autonomous Robotic Systems Using Interval Type-2 Fuzzy Logic and Genetic Algorithms.- 17 Adaptive Noise Cancellation Using Type-2 Fuzzy Logic and Neural Networks.

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