NDLI: A kind of monotonic similarity measure of interval-valued fuzzy sets

Content Provider	IEEE Xplore Digital Library
Author	Guannan Deng LianLian Song Yanli Jiang Jingchao Fu
Copyright Year	2015
Description	Author affiliation: Coll. of Sci., Northeast Dianli Univ. Jilin, Jilin, China (Guannan Deng; LianLian Song; Yanli Jiang; Jingchao Fu)
Abstract	A similarity measure is a measure that indicates the degree of similarity between two objects. This paper investigates the monotonicity properties of similarity measures of interval-valued fuzzy sets. Firstly, a new kind of similarity measure, named monotonic similarity measure is proposed and investigated through analyzing the geometrical relation between interval-valued fuzzy sets. Furthermore, its properties and relationship with entropy and inclusion measure are studied and discussed. And then, some mew monotonic similarity measures are constructed by means of the proposed relationship. Finally, the applications of the proposed monotonic similarity measures are presented. This research not only introduces a novel kind of similarity measure, but also provides some methods to construct similarity measures, entropies and inclusion measures.
Starting Page	1
Ending Page	4
File Size	116095
Page Count	4
File Format	PDF
e-ISBN	9781467376822
DOI	10.1109/FSKD.2015.7381903
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy sets Inclusion measure Interval-valued fuzzy set Monotonic similarity measure Area measurement Measurement uncertainty Knowledge discovery Entropy Risk analysis Fuzzy systems
Content Type	Text
Resource Type	Article

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