A new method for similarity measures for pattern recognition

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/106073

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106073

Title:	A new method for similarity measures for pattern recognition
Authors:	范國清;Yen, Peter C.P.;Fan, KuoChin;Chao, Henry C.J.
Contributors:	資訊電機學院資訊工程學系
Keywords:	Axioms;Fuzzy set theory;Handles;Intuitionistic fuzzy sets;Mathematical analysis;Mathematical models;Pattern recognition;Similarity;Similarity measures
Date:	2013-04-01
Issue Date:	2026-04-23 13:07:38 (UTC+8)
Publisher:	Elsevier Inc.;Elsevier Inc
Abstract:	摘要： This paper points out three questionable areas in the realm of similarity measures and then provides a new method that will rectify the problem. The purpose of this paper is fourfold. First, we will propose a scenario where the three similarity measures proposed by Hung and Yang (2004) [1] are helpless in aiding a decision maker in deciding pattern recognition problem. Second, we will present our method for solving the dilemma. Third, we will show that our proposed similarity measures satisfy the axioms for well defined similarity measures. Fourth, we will prove that our method could solve pattern recognition problems. Our findings will help researchers handle similarity problems under intuitionistic fuzzy sets environment. 出版者： Elsevier Inc 出版日期： 2013-04-01 出處： Applied mathematical modelling, 2013-04, Vol.37 (7), p.5335-5342 資源來源： ScienceDirect - Freedom Collection 版權： 2012 Elsevier Inc. 識別號： ISSN: 0307-904X 識別號： DOI: 10.1016/j.apm.2012.10.043
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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