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An Ontological and Epistemological Perspective of Fuzzy Set Theory
ID: 170511
I. Burhan Türksen
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Fuzzy set and logic theory. Linguistic expressions are imprecise and must be considered as a matter of degree. The decision in schemas is a human decision. Even if the membership functions are restricted to be Type1, their combinations generate an interval - valued Type 2 membership. This is a part of the general result. Classical equivalences breakdown in Fuzzy theory. Thus, all classical formulas must be reassessed with the classical formulas.
Key features:
- Ontological grounding
- Epistemological justification
- Measurement of Membership
- Breakdown of equivalences
- FDCF is not equivalent to FCCF
- Fuzzy Beliefs
- Meta-Linguistic axioms
- Ontological grounding
- Epistemological justification
- Measurement of Membership
- Breakdown of equivalences
- FDCF is not equivalent to FCCF
- Fuzzy Beliefs
- Meta-Linguistic axioms
Table of Contents
Preface
Table of Contents
0. Foundation
1. Introduction
2. Computing with Words
3. Measurement of Membership
4. Elicitation Methods
5. Fuzzy Clustering Methods
6. Classes of Fuzzy Set and Logic Theories
7. Equivalences in Two-Valued Logic
8. Fuzzy-Valued Set and Two-Valued Logic
9. Containment of FDCF in FCCF
10. Consequences of D (0,1), V (0,1) Theory
11. Compensators "And"
12. Belief, Plausibility and Probability Measures on Interval-Valued Type 2 Fuzzy Sets
13. Veristic Fuzzy Sets of Truthoods
14. Approximate Reasoning
15. Interval-Valued Type 2 GMP
16. A Theoretical Application of Interval-Valued Type 2 Representation
17. A Foundation for Computing with Words: Meta-Linguistic Axioms
18. Epilogue
References
Subject Index
Author Index
170511
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I. Burhan Türksen