Therefore, this paper proposes a novel, simple, and intuitive approach to distance and similarity measures for q-ROFSs based on belief and plausibility functions within the framework of ET. This research addresses a significant research gap by introducing a comprehensive framework for handling ...
Rogers, "Similarity and distance measures for cellular manufacturing. Part II: An extension and comparison", IJPR 31 (6), 1315-1326 (1993).Shafer SM, Rogers DF (1993) Similarity and distance measures for cellular manufacturing, part II: an extension and comparison. Int J Prod Res 31(6):...
toillustratethesedistanceandsimilaritymeasures. Hesitantfuzzyset 2011ElsevierInc.s. Distancemeasure Similaritymeasure Decisionmaking 1.Introduction Whenpeoplemakeadecision,theyareusuallyhesitantandirresoluteforhingoranotherwhiakesitdifficultto reachafinalagreement.Forexample,twodecisionmakersdiscussthemembershipdegree...
The basis of many measures of similarity and dissimilarity is euclidean distance. The distance between vectors X and Y is defined as follows: In other words, euclidean distance is the square root of the sum of squared differences between corresponding elements of the two vectors. Note that the ...
Minkowski Distance: It is a generic distance metric where Manhattan(r=1) or Euclidean(r=2) distance measures are generalizations of it. Manhattan Distance: It is the sum of absolute differences betw…
and Kacprzyk[38]proposed four distance measures between vague sets,which were in some extent based on the geometric interpretation of intuitionistic fuzzy sets,and have some good geometric properties.Wang and Xin[40]provided a more generalized de,nition of distance measures between intuitionistic fuzzy...
These distance measures in the literature for hesitant fuzzy sets and hesitant fuzzy elements are only taken into account the difference between the membership values, but the difference of hesitance degree between the hesitant fuzzy elements is not considered. In fact, hesitancy is the most ...
The dissimilarity measures tested are L 1 norm, median of absolute differences, square L 2 norm, median of square differences, normalized square L 2 norm, incremental sign distance, intensity-ratio variance, intensity-mapping-ratio variance, rank distance, joint entropy, and exclusive F -...
Xu and Xia, 2011b, Xu and Xia, 2011a first proposed the distance axiom, the similarity axiom, distance measure models and similarity models for hesitant fuzzy sets. Considering the transitive property of distance measures, Li et al. (2015) improved the distance axiom and distance measure ...
A library implementing different string similarity and distance measures. A dozen of algorithms (including Levenshtein edit distance and sibblings, Jaro-Winkler, Longest Common Subsequence, cosine similarity etc.) are currently implemented. Check the summary table below for the complete list... ...