Concept
Ensemble flou
Concepts associés (16)
Théorie des ensembles approximatifs
Théorie des ensembles approximatifs – est un formalisme mathématique proposé en 1982 par le professeur Zdzisław Pawlak. Elle généralise la théorie des ensembles classique. Un ensemble approximatif (anglais : rough set) est un objet mathématique basé sur la logique 3 états. Dans sa première définition, un ensemble approximatif est une paire de deux ensembles : une approximation inférieure et une approximation supérieure. Il existe également un type d'ensembles approximatifs défini par une paire d'ensembles flous (anglais : fuzzy set).
Logique floue
La logique floue (fuzzy logic, en anglais) est une logique polyvalente où les valeurs de vérité des variables — au lieu d'être vrai ou faux — sont des réels entre 0 et 1. En ce sens, elle étend la logique booléenne classique avec des . Elle consiste à tenir compte de divers facteurs numériques pour qu'on souhaite acceptable.
Type-2 fuzzy sets and systems
Type-2 fuzzy sets and systems generalize standard Type-1 fuzzy sets and systems so that more uncertainty can be handled. From the beginning of fuzzy sets, criticism was made about the fact that the membership function of a type-1 fuzzy set has no uncertainty associated with it, something that seems to contradict the word fuzzy, since that word has the connotation of much uncertainty. So, what does one do when there is uncertainty about the value of the membership function? The answer to this question was provided in 1975 by the inventor of fuzzy sets, Lotfi A.
Fonction caractéristique (théorie des ensembles)
En mathématiques, une fonction caractéristique, ou fonction indicatrice, est une fonction définie sur un ensemble E qui explicite l’appartenance ou non à un sous-ensemble F de E de tout élément de E. Formellement, la fonction caractéristique d’un sous-ensemble F d’un ensemble E est une fonction : D'autres notations souvent employées pour la fonction caractéristique de F sont 1 et 1, voire I (i majuscule). Le terme de fonction indicatrice est parfois utilisé pour fonction caractéristique.
Alternative set theory
In a general sense, an alternative set theory is any of the alternative mathematical approaches to the concept of set and any alternative to the de facto standard set theory described in axiomatic set theory by the axioms of Zermelo–Fraenkel set theory. More specifically, Alternative Set Theory (or AST) may refer to a particular set theory developed in the 1970s and 1980s by Petr Vopěnka and his students.
Fuzzy set operations
Fuzzy set operations are a generalization of crisp set operations for fuzzy sets. There is in fact more than one possible generalization. The most widely used operations are called standard fuzzy set operations; they comprise: fuzzy complements, fuzzy intersections, and fuzzy unions. Let A and B be fuzzy sets that A,B ⊆ U, u is any element (e.g. value) in the U universe: u ∈ U. Standard complement The complement is sometimes denoted by ∁A or A∁ instead of ¬A.
T-norm
In mathematics, a t-norm (also T-norm or, unabbreviated, triangular norm) is a kind of binary operation used in the framework of probabilistic metric spaces and in multi-valued logic, specifically in fuzzy logic. A t-norm generalizes intersection in a lattice and conjunction in logic. The name triangular norm refers to the fact that in the framework of probabilistic metric spaces t-norms are used to generalize the triangle inequality of ordinary metric spaces.
Symmetric difference
In mathematics, the symmetric difference of two sets, also known as the disjunctive union, is the set of elements which are in either of the sets, but not in their intersection. For example, the symmetric difference of the sets and is . The symmetric difference of the sets A and B is commonly denoted by or The power set of any set becomes an abelian group under the operation of symmetric difference, with the empty set as the neutral element of the group and every element in this group being its own inverse.
Neuro-fuzzy
In the field of artificial intelligence, the designation neuro-fuzzy refers to combinations of artificial neural networks and fuzzy logic. Neuro-fuzzy hybridization results in a hybrid intelligent system that combines the human-like reasoning style of fuzzy systems with the learning and connectionist structure of neural networks. Neuro-fuzzy hybridization is widely termed as fuzzy neural network (FNN) or neuro-fuzzy system (NFS) in the literature.
Système intelligent flou
Un système intelligent flou (SIF) est un système qui intègre (implémente) de l’expertise humaine et qui vise à automatiser (imiter) le raisonnement d’experts humains face à des systèmes complexes. Il constitue une part importante de l’intelligence artificielle et du soft computing. Un système intelligent flou se base sur la théorie logique qu'est la logique floue.