Title :
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
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;
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
DOI :
10.1109/ICMTMA.2010.638
