{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T04:55:05Z","timestamp":1778734505908,"version":"3.51.4"},"reference-count":22,"publisher":"Emerald","issue":"4","license":[{"start":{"date-parts":[[2018,8,20]],"date-time":"2018-08-20T00:00:00Z","timestamp":1534723200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["GS"],"published-print":{"date-parts":[[2018,9,24]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>The purpose of this paper is to study the modelling mechanisms of several grey incidence analysis models with great influence, including Deng\u2019s grey incidence model, absolute degree of grey incidence model, slope degree of incidence model, similitude degree of incidence model and closeness degree of incidence model; then analyse the problems to be solved in grey incidence analysis models; and clarify the applicable ranges of commonly used grey incidence models.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>The paper comes to conclusions by means of comparable analysis. The authors compare several commonly used grey incidence analysis models, including Deng\u2019s grey incidence model, absolute degree of grey incidence model, slope degree of incidence model, similitude degree of incidence model and closeness degree of incidence model and give several examples to clarify the reasons why quantitative analysis results of different models are not exactly the same.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>As the intension of each kind of incidence model is clear and the extension is relatively obscure, grey incidence orders calculated by different incidence models are often different. When making actual decisions, incompatible results may appear. According to different characteristics of extraction, grey incidence analysis models can be divided into three types: incidence model based on closeness perspective, incidence model based on similarity perspective and incidence model based on comprehensive perspective.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title>\n<jats:p>The conclusions obtained in this paper can help people avoid some defects in the process of actual selection and choose the better incidence analysis model.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The conclusions can be used as a reference and basis for the selection of grey incidence analysis models, it can help to overcome the defects and shortcomings of models caused by themselves and screen out more excellent analytical models.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/gs-04-2018-0019","type":"journal-article","created":{"date-parts":[[2018,8,20]],"date-time":"2018-08-20T10:19:58Z","timestamp":1534760398000},"page":"448-461","source":"Crossref","is-referenced-by-count":16,"title":["On modeling mechanisms and applicable ranges of grey incidence analysis models"],"prefix":"10.1108","volume":"8","author":[{"given":"Wenjie","family":"Dong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sifeng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhigeng","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2018,8,20]]},"reference":[{"key":"key2021041413352385400_ref001","first-page":"47","article-title":"Improvement on calculation of generalized absolute grey relational grade based on the point-wise annihilating operator","year":"2009"},{"issue":"1","key":"key2021041413352385400_ref002","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/ijmfmp.2015010101","article-title":"Optimization of WEDM process parameters for MRR and surface roughness using Taguchi-based grey relational analysis","volume":"2","year":"2015","journal-title":"International Journal of Materials Forming & Machining Processes"},{"issue":"1","key":"key2021041413352385400_ref003","first-page":"1","article-title":"Introduction to grey system theory","volume":"1","year":"1989","journal-title":"Journal of Grey System"},{"key":"key2021041413352385400_ref004","first-page":"149","article-title":"Control and optimization of quality cost based on discrete grey forecasting model","year":"2017"},{"issue":"3","key":"key2021041413352385400_ref005","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1108\/GS-06-2017-0016","article-title":"Study of a discrete grey forecasting model based on the quality cost characteristic curve","volume":"7","year":"2017","journal-title":"Grey Systems: Theory and Application"},{"issue":"4","key":"key2021041413352385400_ref006","first-page":"685","article-title":"Grey incidence decision making model based on area","volume":"30","year":"2015","journal-title":"Control & Decision"},{"key":"key2021041413352385400_ref007","volume-title":"Grey Systems Theory and Its Applications","year":"2017","edition":"8th ed."},{"issue":"1","key":"key2021041413352385400_ref008","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1108\/20439371111106696","article-title":"Novel models of grey relational analysis based on visual angle of similarity and nearness","volume":"1","year":"2011","journal-title":"Grey Systems: Theory and Application"},{"key":"key2021041413352385400_ref009","volume-title":"Grey Incidence Analysis Models. 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