Nonlinear Prediction of Gross Industrial Output Time Series by Gradient Boosting

摘要：

Predicting gross industrial production is helpful to design plan in development zone. History data in Jinchuan district, Hohhot, were collected. BDS, Ljung-Box, Box-Pierce, Whites and Teraesvirtas neural network test and surrogate data test were combined to selecting a proper model. According to phase space reconstruction, function fitting was finished by Gradient Boosting. The results showed that nonlinear dependence existed in series. The production in 2015 was predicted to be 6937977 ten thousand Yuan.

作者: Rui ZHANG Hong-li WANG

作者单位: School of Management, Tianjin University, Tianjin, P.R.China

会议类型: 国际会议

会议名称: 2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management(2011 IEEE 第十八届工业工程与工程管理国际会议 IEEM2011)

会议地点: 长春

会议语种:英文

页码: 153-156

在线出版日期: 2011-09-03（万方平台首次上网日期，不代表论文的发表时间）