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fuzzification porzvâreš Fr.: fuzzification The first step carried out in a → fuzzy logic system during which a → crisp set of → input data are gathered and converted to a → fuzzy set using fuzzy → linguistic variables, fuzzy linguistic terms, and → membership functions. |
fuzzify pozvâridan Fr.: fuzzifier To convert a → crisp set to a → fuzzy set in a → fuzzy logic system. |
fuzziness porzvâri Fr.: The state or condition of being → fuzzy. |
fuzzy porzvâr Fr.: flou, crépu 1) Of the nature of or resembling → fuzz. From → fuzz + -y adj. suffix, from O.E. -ig, cognate with L. -icus, → -ic. Porzvâr "resembling fuzz," from porz, → fuzz, + -var, a suffix of possession, similarity, and aptitude (e.g., omidvâr, sezâvâr, sugvâr, šâhvâr, gušvâr), → -oid. |
fuzzy image tasvir-e porzvâr Fr.: image floue, ~ estompée Same as → blurred image. |
fuzzy inference system râžmân-e darbord-e porzvâr Fr.: A way of → mapping an → input space to an → output space using → fuzzy logic. FIS uses a collection of fuzzy → membership functions and rules, instead of Boolean logic, to reason about data. Also called → fuzzy logic system. |
fuzzy inferencing darbord-e porzvâr Fr.: A process used in a → fuzzy logic system where the → truth value for the premise of each rule is computed and applied to the conclusion part of each rule. This results in one fuzzy set to be assigned to each output variable for each rule. |
fuzzy logic guyik-e porzvâr Fr.: logic flou A mathematical logic that recognizes more than simple → true and → false → propositions. With fuzzy logic, propositions can be represented with degrees of truthfulness and falsehood. In this system, → truth values are → fuzzy sets without sharp boundaries (→ crisp set) in contrast with → classical logic. Fuzzy logic is applied to a wide range of problems including: industrial control, domestic goods, decision making, robotics, intelligent machines, and image processing in medicine. |
fuzzy logic system râžmân-e guyik-e porzvâr Fr.: système de logic flou An engineering system which uses → fuzzy logic. It generally consists of four main components: → fuzzification interface (fuzzifier), → fuzzy rule base, → fuzzy inferencing unit, and → defuzzification interface (difuzzifier). Also called → fuzzy inference system. |
fuzzy rule base pâygâh-e razan-e porzvâr Fr.: A rule base in a → fuzzy logic system constructed to control the → output variable. A fuzzy rule is a simple if-then rule with a condition and a conclusion. |
fuzzy set hangard-e porzvâr Fr.: ensemble flou A set of → truth values in → fuzzy logic that does not have sharp boundaries. Instead, set members have degrees of membership. If the value of 1 is assigned to objects entirely within the set and a 0 is assigned to objects outside of the set, then any object partially in the set will have a value between 0 and 1. This contrast with → crisp sets in → classical logic where members assume a precise value of 1 or 0. Fuzzy sets were first introduced by Lotfi A. Zadeh (1965) and defined as follows. Let X be a space of points, with a generic element of X denoted by x. Thus X = {x}. A fuzzy set A in X is characterized by a → membership function f_{A}(x) which associates with each point in X a real number in the interval [0,1], with the values of f_{A}(x) at x representing the "grade of membership" of x in A. Thus, the nearer the value of f_{A}(x) to unity, the higher the grade of membership of x in A. Generally, the intersection operations of fuzzy sets are the expansion of that operation on → nonfuzzy sets. In other words, operations on nonfuzzy sets are a particular case of operations on fuzzy sets. |
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