Download An Ontological and Epistemological Perspective of Fuzzy Set by I. Burhan Türksen PDF

By I. Burhan Türksen

Fuzzy set and common sense thought recommend that every one traditional language linguistic expressions are obscure and needs to be assessed as an issue of measure. yet regularly club measure is an obscure inspiration which calls for that style 2 club levels be thought of in such a lot functions on the topic of human selection making schemas. whether the club services are constrained to be Type1, their mixtures generate an period - valued sort 2 club. this can be a part of the overall outcome that Classical equivalences breakdown in Fuzzy idea. therefore all classical formulation needs to be reassessed with an higher and reduce expression which are generated via the breakdown of classical formulation.

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That is, the object seems to be just what it is factually; it is not ambiguous, or imprecise in itself, only in our misperceptions of it or in our measurement errors of it. This naturally discards the "Principle of Uncertainty" proposed and verified on the level of atomic physics by Heisenberg. It is interesting, to note, however, in the case of the Domain-Specific Epistemology endorsed by classical thinking, such "objective facts of the world" (which by definition stand as true, regardless of our will, mood, or perception on them) may include both external states in the world as well as certain "internal" (though nevertheless still "objective"), be abstract, states or realities.

4. Philosophical Comparison among Different Fuzzy Theories The standard approach taken by the proposed hierarchical sketch method may be particularly useful for comparing the philosophical bases of different fuzzy theories. This helps to structure our observations about the fuzzy theories and lends itself readily for making comparisons amongst them. Diverse fuzzy theories may appear to differ primarily at one level of the hierarchy or at times at many levels of inquiry. Most common comparison of fuzzy theories will, of course, focus primarily on their differences of emphasis and approach at the Application Level 7 of Fuzzy Logic.

They may entail re-computations of, say, fuzzy regression, or fuzzy programming, or fuzzy control models with, test data. Results obtained from such models are assumed to be on {D[o,i] V{o,i}} framework for descriptive fuzzy set models based on some level of risk and on {V[o,i] V'{o,i}} framework for veristic fuzzy logic models. However, it is to be noted that, at this juncture most fuzzy theory applications are verified and/or validated still with classical statistical measures such as, RMSE, R^ accuracy and power of prediction that is stated in the classical theories "Domain Specific" verification, validation exercises.

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