DocumentCode
2171815
Title
The Forecast of Coal Demand Based on RoughSet and BP Neural Network Model
Author
Zhenyu Cai ; Ma, Xingmin
Author_Institution
Sch. of Econ. & Manage., HeBei Univ. of Eng., Handan, China
fYear
2010
fDate
24-26 Aug. 2010
Firstpage
1
Lastpage
4
Abstract
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; supply and demand; BP neural network model; China; backpropagation; coal demand forecasting; rough set theory; Artificial neural networks; Biological system modeling; Decision making; Fuel processing industries; Predictive models; Set theory; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Management and Service Science (MASS), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5325-2
Electronic_ISBN
978-1-4244-5326-9
Type
conf
DOI
10.1109/ICMSS.2010.5577120
Filename
5577120
Link To Document