Results 271 to 280 of about 247,756 (301)

Rule extraction for fuzzy modeling

Fuzzy Sets and Systems, 1997
Abstract In this paper, a method based on genetic algorithms is proposed to automatically extract fuzzy rules to identify a system where only its input-output data are available. This method can determine a fuzzy system with fewer fuzzy rules as well as the antecedent and consequent parameters of the fuzzy rules at the same time.
Ching-Chang Wong, Nine-Shen Lin
openaire   +1 more source

Fuzzy Classifier with Probabilistic IF-THEN Rules

2007
The typical fuzzy classifier consists of rules each one describing one of the classes. This paper presents a new fuzzy classifier with probabilistic IF-THEN rules. A learning algorithm based on the gradient descent method is proposed to identify the probabilistic IF-THEN rules from the training data set.
Hexin Lv, Bin Zhu, Yongchuan Tang
openaire   +1 more source

Induction of fuzzy production rules

Proceedings of the Twentieth International Symposium on Multiple-Valued Logic, 2002
The problem of inducing new production rules from a rule bank of an expert system is treated. Criteria and methods for such an induction are proposed for rules with Boolean premises and conclusion and with certainty factors. The results are extended to rules with fuzzy expressions as premises and conclusions and with certainty factors for them ...
O. O. Silva, C. R. Souza
openaire   +1 more source

A metasemantics to refine fuzzy if-then rules

Proceedings. 34th International Symposium on Multiple-Valued Logic, 2004
Fuzzy if-then rules are used to represent fuzzy models. Real data is later used to tune the model. Usually this forces a modification of the initial linguistic terms of the linguistic variables used for the model. Such modifications may lead to a loss in interpretability of the rules.
openaire   +1 more source

Fuzzy rules

2022
András Bárdossy, Lucien Duckstein
openaire   +1 more source

Safe Modelling of Fuzzy If-Then Rules

2006
Nowadays, it is not necessary to advocate in favor of systems of fuzzy IFTHEN rules, because they are widely used in applications of fuzzy set theory such that fuzzy control, identification of dynamic systems, prediction of dynamic systems, decision-making, etc.
Irina Perfilieva, Stephan Lehmke
openaire   +1 more source

Measure Inputs to Fuzzy Rules

2014
Our concern is with the determination of the firing level of the antecedent fuzzy set in a fuzzy systems model rule base. We first consider the case where the input information is also expressed in terms of a normal fuzzy set. We provide the requirements needed by any formulation of this operation.
openaire   +1 more source

What are fuzzy rules and how to use them

Fuzzy Sets and Systems, 1996
Didier Dubois, Henri Prade
exaly  

Improving Generalization of Fuzzy IF--THEN Rules by Maximizing Fuzzy Entropy

IEEE Transactions on Fuzzy Systems, 2009
Xizhao Wang, Chun-Ru Dong
exaly  

The CALCULUS of Fuzzy If/Then RULES

1993
openaire   +1 more source