Application of Partial Least-square Regression to Engine Maintenance Project Cost Forecasting

摘要：

The traditional multivariate regression methods cannot get satisfactory results as the impact of engine maintenance project cost forecasting by multiple and complex factors, and the sample data scarcity. This article proposes a Partial Leastsquare Regression model (PLSR, for short).PLSR has prominent advantages in dealing with small samples and variables with multiple relevance. The instance shows that PLSR is a better method, with lower error and higher accuracy. PLSR is a valid method for forecasting engine maintenance project cost and should be applied further.

关键词： engine maintenance project cost forecasting Partial Least-square Regression

作者: Xin LI Rong-xi ZHOU

作者单位: School of Economics and Management,Beijing University of Chemical Technology,Beijing,P.R.China,100029

会议类型: 国际会议

会议名称: The 2nd International Conference on Vale Engineering and Vale Management(2009)(2009年北京价值工程与价值管理国际会议)

会议地点: 北京

会议语种:英文

页码: 189-194

在线出版日期: 2009-10-16（万方平台首次上网日期，不代表论文的发表时间）