FUZZY INFERENCE SYSTEM AND PYTHON - THE TIPPING PROBLEM

Описание: Human beings are capable of dealing with very complex processes, based on inaccurate or approximate information. The strategy adopted by human operators is also imprecise in nature and generally possible to be expressed in linguistic terms. Fuzzy Set Theory and Fuzzy Logic Concepts can be used to translate into mathematical terms the imprecise information expressed by a set of linguistic rules. If a human operator is able to articulate his action strategy as a set of rules of the if-then form, a computer-implementable algorithm can be constructed. The result is a rule-based inference system, in which Fuzzy Set Theory and Fuzzy Logic provide the mathematical tools to deal with such linguistic rules.

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Fuzzy Set Theory was conceived by L. A. Zadeh* with the aim of providing a mathematical tool for the treatment of imprecise or vague information. Fuzzy Logic, based on this theory, was initially built from the already established concepts of classical logic; Operators were defined similarly to those traditionally used and others were introduced over time, often due to eminently practical needs.

*Zadeh, L.A. (1965). Fuzzy Sets. Information and Control, vol. 8: pp. 338-353.

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