Hanat Y. Raji-Lawal , Adio T. Akinwale , Olusegun Folorunsho , Amidu O. Mustapha
{"title":"Decision support system for dementia patients using intuitionistic fuzzy similarity measure","authors":"Hanat Y. Raji-Lawal , Adio T. Akinwale , Olusegun Folorunsho , Amidu O. Mustapha","doi":"10.1016/j.socl.2020.100005","DOIUrl":null,"url":null,"abstract":"<div><p>Similarity measure confirms the proximity of two objects to each other. This concept can be applied as fuzzy or intuitionistic fuzzy. There are lots of fuzzy similarity measures which had been extended to intuitionistic fuzzy similarity measure, with application in different domain. There is need to investigate these methods based on their application for further modification. Thus, the aim of this research is to modify existing fuzzy and intuitionistic fuzzy similarity measures, and apply it to cognitive domain for better performance.</p><p>Existing intuitionistic fuzzy similarity methods were extended and modified. These research showed that the existing methods had been applied to various domains, and researchers had improved and extended most fuzzy similarity measure to intuitionistic fuzzy similarity measure for optimal performance. Experiment showed that the proposed methods gives higher similarity value and lower processing time.</p></div>","PeriodicalId":101169,"journal":{"name":"Soft Computing Letters","volume":"2 ","pages":"Article 100005"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.socl.2020.100005","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soft Computing Letters","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666222120300046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/6/20 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Similarity measure confirms the proximity of two objects to each other. This concept can be applied as fuzzy or intuitionistic fuzzy. There are lots of fuzzy similarity measures which had been extended to intuitionistic fuzzy similarity measure, with application in different domain. There is need to investigate these methods based on their application for further modification. Thus, the aim of this research is to modify existing fuzzy and intuitionistic fuzzy similarity measures, and apply it to cognitive domain for better performance.
Existing intuitionistic fuzzy similarity methods were extended and modified. These research showed that the existing methods had been applied to various domains, and researchers had improved and extended most fuzzy similarity measure to intuitionistic fuzzy similarity measure for optimal performance. Experiment showed that the proposed methods gives higher similarity value and lower processing time.