Rough Set-BP neural network model in the application of the coal demand forecast

摘要：

The energy of coal as the basis for rapid economic development plays a supporting role. In the past, the accuracy of forecasting coal demand is not very satisfactory. In this paper, rough set for the coal demand factors affecting the reduction, the core factors extracted using BP neural network to predict, through the results of China coal demand forecast can be seen that the value of history fit very well, indicating that this model has better scientific and rationality. Finally, the model predicts the next four years coal demand in China.

关键词： rough set attribute reduction BP neural network Forecast

作者: Xuanchi Zhou Xiaodong Zhu Jun-e Liu

作者单位: Department Beijing WUZI University, Beijing, China Information School Beijing WUZI University Beijing, China

会议类型: 国际会议

会议名称: 2010 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2010)(2010年检测技术与机电自动化国际会议)

会议地点: 长沙

会议语种:英文

页码: 2553-2556

在线出版日期: 2010-03-13（万方平台首次上网日期，不代表论文的发表时间）