Introduction to Fuzzy Sets

H.-J. Zimmermann

Chapter 1 in Fuzzy Set Theory—and Its Applications, 1996, pp 1-7 from Springer

Abstract: Abstract Most of our traditional tools for formal modeling, reasoning, and computing are crisp, deterministic, and precise in character. By crisp we mean dichotomous, that is, yes-or-no-type rather than more-or-less type. In conventional dual logic, for instance, a statement can be true or false—and nothing in between. In set theory, an element can either belong to a set or not; and in optimization, a solution is either feasible or not. Precision assumes that the parameters of a model represent exactly either our perception of the phenomenon modeled or the features of the real system that has been modeled. Generally, precision also implies that the model is unequivocal, that is, that it contains no ambiguities.

Keywords: Modeling Language; Mathematical Language; Logical Language; Subjective Category; Logical Symbol (search for similar items in EconPapers)
Date: 1996
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DOI: 10.1007/978-94-015-8702-0_1

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