DocumentCode
2418978
Title
Coal Requirement Prediction Using BP Neural Network
Author
Xuxin ; Xu Lihong
Author_Institution
Manage. Dept., Univ. of Shanghai Sci. & Technol., Shanghai, China
fYear
2010
fDate
7-9 May 2010
Firstpage
3815
Lastpage
3818
Abstract
Coal is one of the most important main energy-consuming resources in our society. It is important to forecast the coal requirement with high accuracy. BP neural network forecasting model has the typical of self-learning and self-adaptation. It is often used in these systems that are difficult to create accurate mathematical model. The factors such as the trend of the industrial coal, the rate of increased GDP, rice index and the proportion in the energy-consuming of coal are considered in this paper. We use improved BP model to predict and simulate in MATLAB. It proves that this prediction has better application.
Keywords
backpropagation; coal; demand forecasting; forecasting theory; neural nets; BP neural network; Matlab; coal; forecasting model; requirement prediction; self-adaptation; self-learning; Artificial neural networks; Economic indicators; Finance; Indexes; MATLAB; Mathematical model; Predictive models; BP neural network; MATLAB; coal demand prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-0-7695-3997-3
Type
conf
DOI
10.1109/ICEE.2010.956
Filename
5591798
Link To Document