[PDF] Top 20 A bidirectional subsethood based similarity measure for fuzzy sets

... about fuzzy sets. Hence, many classical set-theoretic similarity measures have been extended for comparing fuzzy ...set-theoretic similarity measure considering the ... See full document

... distance measure, similarity measure and entropy of fuzzy sets and IFSs gained importance since their introduction by Zadeh [12] and Atanassov [1] ...moments. Similarity of two ... See full document

... of fuzzy sets [3]. Fuzzy entropy is one of the most important methods to measure the degree of disorder in fuzzy sets, and knowledge measure is one of the most important ... See full document

... Distance measure is a term that describes the difference between intuitionistic fuzzy sets and can be considered as a dual concept of similarity ...intuitionistic fuzzy sets, ... See full document

... tangent similarity measure of fuzzy sets is proposed and its properties are ...tangent similarity measure of fuzzy sets is a decision making tool which is ... See full document

... rough sets [6], [7], belief struc- ture [8]–[10], entropy function [11]–[15], Z numbers [16], [17] and D numbers [18]–[22] are presented and are wildly used in lots of real ...tools, fuzzy sets ... See full document

... and similarity measure of IFSs by several authors like ...works. Based on Hamming distance, Szmidt and Kacprzyk [7, 8, 9] introduced the distance and similarity measure between IFSs and ... See full document

... of similarity between interval-valued fuzzy numbers [4], [5], [6], [7], [8], ...existing similarity measures have some ...of similarity between two interval-valued fuzzy numbers in some ... See full document

... matching. Similarity measure or distance measure is also an important factor in assessing the quality of a face recognition ...of similarity measure based on the Lp metric ... See full document

... classic fuzzy set is intuitionistic fuzzy set theory, which was introduced by Atanassov ...intuitionistic fuzzy sets, generalization of intuitionistic fuzzy rough approximation ... See full document

... 1) Demonstration 2: For this demonstration, each interval T2 FS in Fig. 3 was altered into a standard general T2 FS with a principal MF as shown in Fig. 4(a), which displays the set A. Each set has a triangular secondary ... See full document

... new Similarity measure for Fuzzy sets based on the extended definition of complementation using reference function where it is believed that Fuzzy membership function and ... See full document

... novel Similarity measure for Iintuitionistic fuzzy multi sets (IFMS) based on Zhang and Fu’s measure, as Similarity Measure is an important topic in fuzzy ... See full document

... outcome based education, each question test should have certain bloom taxonomy of cognitive objectives that indicates the level of student’s thinking and other specific criteria which describe the question items ... See full document

... hybrid Fuzzy Neural Network (FNN) system for function approximation is ...and fuzzy inputs ...the Fuzzy rule based knowledge is translated directly into network ...fuzzy sets. ... See full document

... 1965, Fuzzy set theory was firstly given by Zadeh [20] which is applied in many real applications to handle ...valued fuzzy sets was proposed to capture the uncertainty of grade of ...intuitionistic ... See full document

... cosine similarity measure for single valued neutrosophic sets based on cosine ...the similarity measures of SVNSs for multiple attribute group decision making method with completely ... See full document

... approach based on a fuzzy measure is ...Using fuzzy logic concepts, the problems involved in finding the minimum/maximum of a entropy criterion function are ...to measure the image ... See full document

... In this paper, we introduce the concepts of (L, M)-fuzzy soft quasi-coincident neighborhood spaces where L be a completely distributive lattice with 0 and 1 elements and M be a strictly two- sided, commutative ... See full document

... a fuzzy data clustering task which contains outliers one can use objective functions of a special ...these similarity measures are softer than those for the metrics: ... See full document