Frontiers of Higher Order Fuzzy Sets

1. Front Matter

   Pages i-xiii

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2. A New Fuzzy Disjointing Difference Operator to Calculate Union and Intersection of Type-2 Fuzzy Sets

   • Hooman Tahayori, Alireza Sadeghian

   Pages 1-17

3. Robustness of Higher-Order Fuzzy Sets

   • Mohammad Biglarbegian

   Pages 19-29

4. Fuzzy Sets of Higher Type and Higher Order in Fuzzy Modeling

   • Witold Pedrycz

   Pages 31-49

5. Recent Advances in Fuzzy System Modeling

   • I. Burhan Türkşen

   Pages 51-66

6. On the Use of Participatory Genetic Fuzzy System Approach to Develop Fuzzy Models

   • Yi Ling Liu, Fernando Gomide

   Pages 67-86

7. Fuzzy Modeling of Economic Institutional Rules

   • Christopher Frantz, Martin K. Purvis, Maryam A. Purvis, Mariusz Nowostawski, Nathan D. Lewis

   Pages 87-129

8. Modeling the Uncertainty of a Set of Graphs Using Higher-Order Fuzzy Sets

   • Lorenzo Livi, Antonello Rizzi

   Pages 131-146

9. Time-Series Forecasting via Complex Fuzzy Logic

   • Omolbanin Yazdanbakhsh, Scott Dick

   Pages 147-165

10. Multi-Subject Type-2 Linguistic Summaries of Relational Databases

    • Adam Niewiadomski, Izabela Superson

    Pages 167-181

11. Bio-Inspired Optimization of Interval Type-2 Fuzzy Controller Design

    • Oscar Castillo

    Pages 183-215

12. Image Processing and Pattern Recognition with Interval Type-2 Fuzzy Inference Systems

    • Patricia Melin

    Pages 217-228

13. Big Data Analytic via Soft Computing Paradigms

    • Mo Jamshidi, Barney Tannahill, Yunus Yetis, Halid Kaplan

    Pages 229-258

14. Back Matter

    Pages 259-261

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Frontiers of Higher Order Fuzzy Sets, provides a unified representation theorem for higher order fuzzy sets. The book elaborates on the concept of gradual elements and their integration with the higher order fuzzy sets. This book also is devoted to the introduction of new frameworks based on general T2FSs, IT2FSs, Gradual elements, Shadowed sets and rough sets. Such new frameworks will provide more capable frameworks for real applications. Applications of higher order fuzzy sets in various fields will be discussed. In particular, the properties and characteristics of the new proposed frameworks would be studied. Such frameworks that are the result of the integration of general T2FSs, IT2FSs, gradual elements, shadowed sets and rough sets will be shown to be suitable to be applied in the fields of bioinformatics, business,  management, ambient intelligence, medicine, cloud computing and smart grids.

• Computational Intelligence
• Fuzzy Set Theory
• Fuzzy Systems
• Gradual Elements
• Granular Computing
• Higher Order Fuzzy Sets
• Shadowed Sets
• Soft Computing

• Ryerson University, Toronto, Canada

  Alireza Sadeghian, Hooman Tahayori

Dr. Alireza Sadeghian, PhD and Dr. Hooman Tahayori, PhD are both professors at Ryerson University

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