{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T01:22:11Z","timestamp":1778462531800,"version":"3.51.4"},"reference-count":20,"publisher":"Emerald","issue":"5\/6","license":[{"start":{"date-parts":[[2012,6,8]],"date-time":"2012-06-08T00:00:00Z","timestamp":1339113600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,6,8]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to simplify the computation of parameter estimation in the grey linear regression model and solve the problem that the development coefficient could not be computed in some sequence data, such as short\u2010term traffic flow.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>Starting from the limitation that can be identified in the equation and analyzing the range using the method to estimate parameters, this paper researches the modelling mechanism and the other forms which are equivalent with the original form. At the same time, this paper gives an estimation method and gets the relationship in various forms and the relationship between the model and GM(1,1) model.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>For the grey linear regression model, there exists a new method of parameter identification and three other forms as follows: the original form, the Whitenization equation and the connotation form.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title><jats:p>The method of parameter identification exposed in the paper expanded the scope of the application of the grey linear regression model, and it can be used to model and forecast the urban road short\u2010time traffic flow.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>This paper has solved some complicated problems such as the parameter estimation computation in the grey linear regression model. In addition, three kinds of representation forms of the model and its relationship between the model and GM(1,1) have also been presented. Finally, its application of the model in a short\u2010term traffic flow prediction has shown its superiority.<\/jats:p><\/jats:sec>","DOI":"10.1108\/03684921211243284","type":"journal-article","created":{"date-parts":[[2014,11,4]],"date-time":"2014-11-04T05:15:22Z","timestamp":1415078122000},"page":"622-632","source":"Crossref","is-referenced-by-count":6,"title":["Grey linear regression model and its application"],"prefix":"10.1108","volume":"41","author":[{"given":"Xinping","family":"Xiao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yayun","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2022032019565996800_b8","unstructured":"Baoqing, M. and Yin, Z. (2008), \u201cApplication of synthetic model of grey theory and linear regression in forecasting for ground subsidence\u201d, Railway Survey, Vol. 5, pp. 20\u20102."},{"key":"key2022032019565996800_b12","doi-asserted-by":"crossref","unstructured":"Bingjun, L. and Chunhua, H. (2007), \u201cThe combined forecasting method of GM(1,1) with linear regression and its application\u201d, Grey Systems and Intelligent Services, pp. 394\u20108.","DOI":"10.1109\/GSIS.2007.4443304"},{"key":"key2022032019565996800_b9","unstructured":"Bingjun, L. and Qiufang, L. (2009), \u201cThe application of grey linear regression model in forecasting for grain production of Henan Province\u201d, Henan Agricultural Sciences, Vol. 10, pp. 44\u20107."},{"key":"key2022032019565996800_b20","unstructured":"Cai Yan, M.D. (2009), Research on Traffic Flow Prediction Based on Grey Prediction Mode, Southwest Jiaotong University, Chengdu."},{"key":"key2022032019565996800_b16","unstructured":"Dexiang, G. and Huihe, S. (2009), \u201cApplication of grey linear regression in the long\u2010term forecast of winterwheat yield\u201d, Journal of Anhui Agricultural Science, Vol. 24, pp. 11337\u20108."},{"key":"key2022032019565996800_b11","unstructured":"Fuwei, Z. and Xuelian, Z. (2008), \u201cGrey\u2010regression variable weight combination model for load forecasting\u201d, Risk Management & Engineering Management, pp. 311\u201016."},{"key":"key2022032019565996800_b1","unstructured":"Julong, D. (2002), The Basis of Grey Theory, Huazhong University of Science & Technology Press, Wuhan."},{"key":"key2022032019565996800_b14","unstructured":"Lurong, W. (2008), \u201cAn optimal grey regression combinatorial model and its applications in China fire's forecasting\u201d, Mathematics In Practice and Theory, Vol. 6, pp. 80\u20104."},{"key":"key2022032019565996800_b19","unstructured":"Sheng, Z. 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