راژمان ِ دربرد ِ پرزوار 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 function*s and rules, instead of
Boolean logic, to reason about data. Also called
→ *fuzzy logic system*. → *fuzzy*; → *inference*;
→ *system*. |

دربرد ِ پرزوار 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*; → *inference*. |

گوییک ِ پرزوار guyik-e porzvâr
*Fr.: logic flou *
A mathematical logic that recognizes more than simple → *true*
and → *false* → *proposition*s.
With fuzzy logic, propositions can be represented with degrees
of truthfulness and falsehood. In this system, → *truth value*s
are → *fuzzy set*s 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*. |

راژمان ِ گوییک ِ پرزوار 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*; → *logic*;
→ *system*. |

پایگاه ِ رزن ِ پرزوار 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*; → *rule*;
→ *base*. |

هنگرد ِ پرزوار hangard-e porzvâr
*Fr.: ensemble flou*
A set of → *truth value*s 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 set*s
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 set*s. In other words, operations on
nonfuzzy sets are a particular case of operations on fuzzy sets. → *fuzzy*; → *set*. |