@article{2959aa3a5fed47b5ae241573dd426801,
title = "A novel multi-information fusion grey model and its application in wear trend prediction of wind turbines",
keywords = "GM(1,1), Information fusion, Non-equidistance, Wear trend, Wind turbine",
author = "Xiaoyu Yang and Zhigeng Fang and Yingjie Yang and David Mba and Xiaochuan Li",
note = "Funding Information: Thank the editors and the anonymous referees for their insightful comments to improve the paper. This work was supported by the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX18_0233), the China Scholarship fund, the National Social Science Foundation of China (12AZD102), the National Natural Science Foundation of China (No. 71671091 , 71701098 ), the Fundamental Research Funds for Central Universities (NJ20150036), the Natural Science Foundation of Jiangsu Province ( BK20160940 ), the Open Fund of postgraduate Innovation Base (Laboratory) at Nanjing University of Aeronautics and Astronautics ( kfjj20170906 ), the Leverhulme Trust International Research Network project (IN-2014-020) and the Royal Society and NSFC International Exchanges project (IEC\NSFC\170391). Publisher Copyright: {\textcopyright} 2019 Elsevier Inc.",
year = "2019",
month = jul,
doi = "10.1016/j.apm.2019.02.043",
language = "English",
volume = "71",
pages = "543--557",
journal = "Applied Mathematical Modelling",
issn = "0307-904X",
publisher = "Elsevier",
}