Topic
Membership function
About: Membership function is a research topic. Over the lifetime, 15795 publications have been published within this topic receiving 418366 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: A new method for determinization of fuzzy finite automata with membership values in complete residuated lattices is introduced and it is shown that determinized automata is closely related to fuzzy right congruences on a free monoid and fuzzy automata associated with them, and in particular, to the Nerode's fuzzyright congruence of a fuzzy automaton.
102 citations
TL;DR: This paper defines similarity and inclusion measures between type-2 fuzzy sets, discusses their properties and also considers the relationships between them, and combines the proposed similarity measures with Yang and Shih's clustering method.
Abstract: In this paper we define similarity and inclusion measures between type-2 fuzzy sets. We then discuss their properties and also consider the relationships between them. Several examples are used to present the calculation of these similarity and inclusion measures between type-2 fuzzy sets. We finally combine the proposed similarity measures with Yang and Shih's [M.S. Yang, H.M. Shih, Cluster analysis based on fuzzy relations, Fuzzy Sets and Systems 120 (2001) 197-212] algorithm as a clustering method for type-2 fuzzy data. These clustering results are compared with Hung and Yang's [W.L. Hung, M.S. Yang, Similarity measures between type-2 fuzzy sets, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 12 (2004) 827-841] results. According to different @a-level, these clustering results consist of a better hierarchical tree.
102 citations
TL;DR: It is shown that the genetic fuzzy classifiers compare favourably with the other classifiers in terms of classification accuracy, and the approximate and descriptive fuzzy rules yield about the same classification accuracy across the different data sets.
102 citations
01 Mar 2011
TL;DR: The interval-valued fuzzy ELECTRE method is presented aiming at solving MCDM problems in which the weights of criteria are unequal, using interval- valued fuzzy set concepts.
Abstract: Decision-making is the process of finding the best option among the feasible alternatives. In classical multiple criteria decision-making (MCDM) methods, the ratings and the weights of the criteria are known precisely. However, if decision makers cannot reach an agreement on the method of defining linguistic variables based on the fuzzy sets, the interval-valued fuzzy set theory can provide a more accurate modeling. In this paper, the interval-valued fuzzy ELECTRE method is presented aiming at solving MCDM problems in which the weights of criteria are unequal, using interval-valued fuzzy set concepts. For the purpose of proving the validity of the proposed model, we present a numerical example and build a practical maintenance strategy selection problem.
102 citations
TL;DR: A way to calibrate the membership functions with comparisons given by the decision-maker on alternatives with known measures is proposed and is illustrated in a study measuring the most important factors in selecting a student current account.
Abstract: Fuzzy AHP is a hybrid method that combines Fuzzy Set Theory and AHP. It has been developed to take into account uncertainty and imprecision in the evaluations. Fuzzy Set Theory requires the definition of a membership function. At present, there are no indications of how these membership functions can be constructed. In this paper, a way to calibrate the membership functions with comparisons given by the decision-maker on alternatives with known measures is proposed. This new technique is illustrated in a study measuring the most important factors in selecting a student current account.
102 citations