基于灰色关联分析的改进TOPSIS方法

Guan-Dao Yang, Lu Sun, Xiao Liu
{"title":"基于灰色关联分析的改进TOPSIS方法","authors":"Guan-Dao Yang, Lu Sun, Xiao Liu","doi":"10.1109/I-SOCIETY16502.2010.6018767","DOIUrl":null,"url":null,"abstract":"The Original TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) Method is a ranking method based on the principle that the chosen alternative should be as close to the ideal solution, rather than the negative-ideal solution, as possible. However, currently utilizing in establishing the evaluation system of indicator-based model, the Original TOPSIS Method is failed to take the weights of indices into account. Besides, other weighting method like Subjective Evaluation Method is proved to be largely influenced by various subjective situations. To resolve the problem of weighting, in this paper, we propose a new method named Modified TOPSIS Method utilizing Gray Correlation Analysis. By eliminating the mistakes caused by indices which are essentially measured by the same factors, it is useful to improve the evaluation system of indicator-based model. The verification utilizing Spearman's Rank Correlation Coefficient demonstrates that our Modified TOPSIS Method is improved.","PeriodicalId":407855,"journal":{"name":"2010 International Conference on Information Society","volume":"166 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Modified TOPSIS Method utilizing the Gray Correlation Analysis\",\"authors\":\"Guan-Dao Yang, Lu Sun, Xiao Liu\",\"doi\":\"10.1109/I-SOCIETY16502.2010.6018767\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Original TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) Method is a ranking method based on the principle that the chosen alternative should be as close to the ideal solution, rather than the negative-ideal solution, as possible. However, currently utilizing in establishing the evaluation system of indicator-based model, the Original TOPSIS Method is failed to take the weights of indices into account. Besides, other weighting method like Subjective Evaluation Method is proved to be largely influenced by various subjective situations. To resolve the problem of weighting, in this paper, we propose a new method named Modified TOPSIS Method utilizing Gray Correlation Analysis. By eliminating the mistakes caused by indices which are essentially measured by the same factors, it is useful to improve the evaluation system of indicator-based model. The verification utilizing Spearman's Rank Correlation Coefficient demonstrates that our Modified TOPSIS Method is improved.\",\"PeriodicalId\":407855,\"journal\":{\"name\":\"2010 International Conference on Information Society\",\"volume\":\"166 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Information Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I-SOCIETY16502.2010.6018767\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Information Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I-SOCIETY16502.2010.6018767","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

原始TOPSIS(通过与理想解决方案相似度排序偏好技术)方法是一种基于所选替代方案应尽可能接近理想解决方案而不是负理想解决方案的原则的排序方法。然而,目前在建立基于指标的模型评价体系时,原有的TOPSIS方法未能考虑到指标的权重。此外,主观评价法等其他加权方法被证明受各种主观情况的影响很大。为了解决权重问题,本文提出了一种基于灰色关联分析的修正TOPSIS方法。通过消除本质上由相同因素衡量的指标所造成的误差,有助于完善基于指标的模型评价体系。利用Spearman秩相关系数的验证表明,改进的TOPSIS方法得到了改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Modified TOPSIS Method utilizing the Gray Correlation Analysis
The Original TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) Method is a ranking method based on the principle that the chosen alternative should be as close to the ideal solution, rather than the negative-ideal solution, as possible. However, currently utilizing in establishing the evaluation system of indicator-based model, the Original TOPSIS Method is failed to take the weights of indices into account. Besides, other weighting method like Subjective Evaluation Method is proved to be largely influenced by various subjective situations. To resolve the problem of weighting, in this paper, we propose a new method named Modified TOPSIS Method utilizing Gray Correlation Analysis. By eliminating the mistakes caused by indices which are essentially measured by the same factors, it is useful to improve the evaluation system of indicator-based model. The verification utilizing Spearman's Rank Correlation Coefficient demonstrates that our Modified TOPSIS Method is improved.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信