{"title":"基于主成分分析的模糊数排序新方法","authors":"Ayad M. Ramadan, Goran Hidayat Kareem","doi":"10.36647/ijsem/09.09.a001","DOIUrl":null,"url":null,"abstract":"It is difficult to rank fuzzy numbers because of their ambiguous values. A few numbers of ranking techniques have been encountered in last few decades. However, existing techniques are situation-dependent which have drawbacks. In this paper we introduced a statistical technique to rank two types of fuzzy numbers, triangular and trapezoidal fuzzy numbers. This technique is the multi-dimensional scaling, more precisely the principal component analysis. Here, we presented each fuzzy numbers as a row in a matrix, then found the scale points in a low dimensions. The scale points are then reconfigured to have a unique representation. The results from this approach are obtained by comparison to the other ranking methods. The validity has been established by comparison with existing works.","PeriodicalId":46578,"journal":{"name":"International Journal of Management Science and Engineering Management","volume":"77 2 1","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Method for Ranking Fuzzy Numbers Based on Principal Component Analysis\",\"authors\":\"Ayad M. Ramadan, Goran Hidayat Kareem\",\"doi\":\"10.36647/ijsem/09.09.a001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is difficult to rank fuzzy numbers because of their ambiguous values. A few numbers of ranking techniques have been encountered in last few decades. However, existing techniques are situation-dependent which have drawbacks. In this paper we introduced a statistical technique to rank two types of fuzzy numbers, triangular and trapezoidal fuzzy numbers. This technique is the multi-dimensional scaling, more precisely the principal component analysis. Here, we presented each fuzzy numbers as a row in a matrix, then found the scale points in a low dimensions. The scale points are then reconfigured to have a unique representation. The results from this approach are obtained by comparison to the other ranking methods. The validity has been established by comparison with existing works.\",\"PeriodicalId\":46578,\"journal\":{\"name\":\"International Journal of Management Science and Engineering Management\",\"volume\":\"77 2 1\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2022-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Management Science and Engineering Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36647/ijsem/09.09.a001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Management Science and Engineering Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36647/ijsem/09.09.a001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
A New Method for Ranking Fuzzy Numbers Based on Principal Component Analysis
It is difficult to rank fuzzy numbers because of their ambiguous values. A few numbers of ranking techniques have been encountered in last few decades. However, existing techniques are situation-dependent which have drawbacks. In this paper we introduced a statistical technique to rank two types of fuzzy numbers, triangular and trapezoidal fuzzy numbers. This technique is the multi-dimensional scaling, more precisely the principal component analysis. Here, we presented each fuzzy numbers as a row in a matrix, then found the scale points in a low dimensions. The scale points are then reconfigured to have a unique representation. The results from this approach are obtained by comparison to the other ranking methods. The validity has been established by comparison with existing works.
期刊介绍：
International Journal of Management Science and Engineering Management (IJMSEM) is a peer-reviewed quarterly journal that provides an international forum for researchers and practitioners of management science and engineering management. The journal focuses on identifying problems in the field, and using innovative management theories and new management methods to provide solutions. IJMSEM is committed to providing a platform for researchers and practitioners of management science and engineering management to share experiences and communicate ideas. Articles published in IJMSEM contain fresh information and approaches. They provide key information that will contribute to new scientific inquiries and improve competency, efficiency, and productivity in the field. IJMSEM focuses on the following: 1. identifying Management Science problems in engineering; 2. using management theory and methods to solve above problems innovatively and effectively; 3. developing new management theory and method to the newly emerged management issues in engineering; IJMSEM prefers papers with practical background, clear problem description, understandable physical and mathematical model, physical model with practical significance and theoretical framework, operable algorithm and successful practical applications. IJMSEM also takes into account management papers of original contributions in one or several aspects of these elements.
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