Rough Set-BP Neural Network Model in the Application of the Coal Demand Forecast

Author

Zhou, Xuanchi ; Zhu, Xiaodong ; Liu, Jun-e

Author_Institution

Postgrad. Dept. Beijing, WUZI Univ., Beijing, China

Volume

3

fYear

2010

fDate

13-14 March 2010

Firstpage

299

Lastpage

302

Abstract

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.

Keywords

backpropagation; coal; demand forecasting; neural nets; rough set theory; China coal demand forecasting; economic development; rough set-BP neural network model; Demand forecasting; Economic forecasting; Energy measurement; Information systems; Mechatronics; Neural networks; Power generation economics; Predictive models; Production; Set theory; BP neural network; Forecast; attribute reduction; rough set;

fLanguage

English

Publisher

ieee

Conference_Titel

Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on

Conference_Location

Changsha City

Print_ISBN

978-1-4244-5001-5

Electronic_ISBN

978-1-4244-5739-7

Type

conf

DOI

10.1109/ICMTMA.2010.638

Filename

5459536