Results 211 to 220 of about 68,709 (264)
Some of the next articles are maybe not open access.
2005
An efficient method for learning membership functions for fuzzy predicates is presented. Positive and negative examples of one class are given together with a system of classification rules. The learned membership functions can be used for the fuzzy predicates occurring in the given rules to classify further examples.
Bergadano F, CUTELLO, Vincenzo
openaire +2 more sources
An efficient method for learning membership functions for fuzzy predicates is presented. Positive and negative examples of one class are given together with a system of classification rules. The learned membership functions can be used for the fuzzy predicates occurring in the given rules to classify further examples.
Bergadano F, CUTELLO, Vincenzo
openaire +2 more sources
Incremental Membership Function Updates
2010Many fuzzy applications today are based on large databases that change dynamically. Particularly, in many flexible querying systems this represents a huge problem, since changing data may lead to poor results in the absence of proper retraining. In this paper we propose a novel incremental approach to represent the membership functions describing the ...
Narjes Hachani +2 more
openaire +1 more source
Membership Functions Generation Based on Density Function
2008 International Conference on Computational Intelligence and Security, 2008Fuzzy membership functions are considered as a key element in fuzzy systems. In order to generate a fuzzy membership function, there are two potential sources: expert knowledge and real data. However expert knowledge acquisition is a difficult issue, on the other hand using real data needs a methodology to translate real data to membership function ...
Imen Derbel +2 more
openaire +1 more source
Why Cauchy Membership Functions: Reliability
Advances in Artificial Intelligence and Machine Learning, 2022An important step in designing a fuzzy system is the elicitation of the membership functions for the fuzzy sets used. Often the membership functions are obtained from data in a traininglike manner. They are expected to match or be at least compatible with those obtained from experts knowledgeable of the domain and the problem being addressed.
Javier Viaña +4 more
openaire +1 more source
Representing membership functions as elements in function space
Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148), 2001This paper generalizes the geometric representation of membership functions comprising a finite number of characteristic points. An extended class of membership functions, satisfying certain monotonicity conditions, can now be expressed as elements in the space of square integrable functions.
Man Lung Wong, Yeung Yam, Péter Baranyi
openaire +1 more source
A new membership function approach to uncertain functions
Fuzzy Sets and Systems, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
A stochastic interpretation of membership functions
Automatica, 1994zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +1 more source
Analytically derived fuzzy membership functions
Cluster Computing, 2017The numerical algorithms typically used for determining the fuzzy membership functions are iterative, might face convergence issues, and lack in the mathematical theory. This study suggests an analytical approach to the determination of fuzzy membership functions via variational optimization.
Weiping Zhang 0001 +4 more
openaire +1 more source
Finding relevant attributes and membership functions
Fuzzy Sets and Systems, 1999Fuzzy systems that automatically derive fuzzy if-then rules from numeric data have been developed. Most have to predefine membership functions in order to learn. Hong and Lee proposed a general learning method that automatically derives fuzzy if-then rules and membership functions from a set of given training examples using a decision table.
Tzung-Pei Hong, Jyh-Bin Chen
openaire +1 more source
Scaling the membership function
European Journal of Operational Research, 1986This paper contains an axiomatic treatment of the measurement of the fuzzy set membership function based on the measurement methodology of the Analytic Hierarchy Process (AHP). The set of axioms corresponding to hierarchic structures are a special case of axioms for priority setting in systems with feedback which allow for a wide class of dependencies.
openaire +2 more sources