Ebook: Advances in Type-2 Fuzzy Sets and Systems: Theory and Applications

This book explores recent developments in the theoretical foundations and novel applications of general and interval type-2 fuzzy sets and systems, including: algebraic properties of type-2 fuzzy sets, geometric-based definition of type-2 fuzzy set operators, generalizations of the continuous KM algorithm, adaptiveness and novelty of interval type-2 fuzzy logic controllers, relations between conceptual spaces and type-2 fuzzy sets, type-2 fuzzy logic systems versus perceptual computers; modeling human perception of real world concepts with type-2 fuzzy sets, different methods for generating membership functions of interval and general type-2 fuzzy sets, and applications of interval type-2 fuzzy sets to control, machine tooling, image processing and diet. The applications demonstrate the appropriateness of using type-2 fuzzy sets and systems in real world problems that are characterized by different degrees of uncertainty.

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This book explores recent developments in the theoretical foundations and novel applications of general and interval type-2 fuzzy sets and systems, including: algebraic properties of type-2 fuzzy sets, geometric-based definition of type-2 fuzzy set operators, generalizations of the continuous KM algorithm, adaptiveness and novelty of interval type-2 fuzzy logic controllers, relations between conceptual spaces and type-2 fuzzy sets, type-2 fuzzy logic systems versus perceptual computers; modeling human perception of real world concepts with type-2 fuzzy sets, different methods for generating membership functions of interval and general type-2 fuzzy sets, and applications of interval type-2 fuzzy sets to control, machine tooling, image processing and diet. The applications demonstrate the appropriateness of using type-2 fuzzy sets and systems in real world problems that are characterized by different degrees of uncertainty.

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This book explores recent developments in the theoretical foundations and novel applications of general and interval type-2 fuzzy sets and systems, including: algebraic properties of type-2 fuzzy sets, geometric-based definition of type-2 fuzzy set operators, generalizations of the continuous KM algorithm, adaptiveness and novelty of interval type-2 fuzzy logic controllers, relations between conceptual spaces and type-2 fuzzy sets, type-2 fuzzy logic systems versus perceptual computers; modeling human perception of real world concepts with type-2 fuzzy sets, different methods for generating membership functions of interval and general type-2 fuzzy sets, and applications of interval type-2 fuzzy sets to control, machine tooling, image processing and diet. The applications demonstrate the appropriateness of using type-2 fuzzy sets and systems in real world problems that are characterized by different degrees of uncertainty.
Content:
Front Matter....Pages i-x
Front Matter....Pages 1-1
Interval Type-2 Fuzzy Logic Systems and Perceptual Computers: Their Similarities and Differences....Pages 3-17
A Survey of Continuous Karnik–Mendel Algorithms and Their Generalizations....Pages 19-31
Two Differences Between Interval Type-2 and Type-1 Fuzzy Logic Controllers: Adaptiveness and Novelty....Pages 33-48
Interval Type-2 Fuzzy Markov Chains....Pages 49-64
zSlices Based General Type-2 Fuzzy Sets and Systems....Pages 65-80
Geometric Type-2 Fuzzy Sets....Pages 81-96
Type-2 Fuzzy Sets and Bichains....Pages 97-112
Type-2 Fuzzy Sets and Conceptual Spaces....Pages 113-129
Front Matter....Pages 131-131
Modeling Complex Concepts with Type-2 Fuzzy Sets: The Case of User Satisfaction of Online Services....Pages 133-146
Construction of Interval Type-2 Fuzzy Sets From Fuzzy Sets: Methods and Applications....Pages 147-163
Interval Type-2 Fuzzy Membership Function Generation Methods for Representing Sample Data....Pages 165-184
Front Matter....Pages 185-185
Type-2 Fuzzy Logic in Image Analysis and Pattern Recognition ....Pages 187-201
Reliable Tool Life Estimation with Multiple Acoustic Emission Signal Feature Selection and Integration Based on Type-2 Fuzzy Logic....Pages 203-217
A Review of Cluster Validation with an Example of Type-2 Fuzzy Application in R....Pages 219-236
Type-2 Fuzzy Set and Fuzzy Ontology for Diet Application....Pages 237-256
Back Matter....Pages 257-262

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This book explores recent developments in the theoretical foundations and novel applications of general and interval type-2 fuzzy sets and systems, including: algebraic properties of type-2 fuzzy sets, geometric-based definition of type-2 fuzzy set operators, generalizations of the continuous KM algorithm, adaptiveness and novelty of interval type-2 fuzzy logic controllers, relations between conceptual spaces and type-2 fuzzy sets, type-2 fuzzy logic systems versus perceptual computers; modeling human perception of real world concepts with type-2 fuzzy sets, different methods for generating membership functions of interval and general type-2 fuzzy sets, and applications of interval type-2 fuzzy sets to control, machine tooling, image processing and diet. The applications demonstrate the appropriateness of using type-2 fuzzy sets and systems in real world problems that are characterized by different degrees of uncertainty.
Content:
Front Matter....Pages i-x
Front Matter....Pages 1-1
Interval Type-2 Fuzzy Logic Systems and Perceptual Computers: Their Similarities and Differences....Pages 3-17
A Survey of Continuous Karnik–Mendel Algorithms and Their Generalizations....Pages 19-31
Two Differences Between Interval Type-2 and Type-1 Fuzzy Logic Controllers: Adaptiveness and Novelty....Pages 33-48
Interval Type-2 Fuzzy Markov Chains....Pages 49-64
zSlices Based General Type-2 Fuzzy Sets and Systems....Pages 65-80
Geometric Type-2 Fuzzy Sets....Pages 81-96
Type-2 Fuzzy Sets and Bichains....Pages 97-112
Type-2 Fuzzy Sets and Conceptual Spaces....Pages 113-129
Front Matter....Pages 131-131
Modeling Complex Concepts with Type-2 Fuzzy Sets: The Case of User Satisfaction of Online Services....Pages 133-146
Construction of Interval Type-2 Fuzzy Sets From Fuzzy Sets: Methods and Applications....Pages 147-163
Interval Type-2 Fuzzy Membership Function Generation Methods for Representing Sample Data....Pages 165-184
Front Matter....Pages 185-185
Type-2 Fuzzy Logic in Image Analysis and Pattern Recognition ....Pages 187-201
Reliable Tool Life Estimation with Multiple Acoustic Emission Signal Feature Selection and Integration Based on Type-2 Fuzzy Logic....Pages 203-217
A Review of Cluster Validation with an Example of Type-2 Fuzzy Application in R....Pages 219-236
Type-2 Fuzzy Set and Fuzzy Ontology for Diet Application....Pages 237-256
Back Matter....Pages 257-262
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