Abstract—In this study, we build a new coal demand
prediction model of tandem gray BP neural network. Firstly we
use 2000-2015 years coal demand data to establish three gray
prediction models: GM(1,1), WPGM(1,1) and pGM(1,1);
Secondly, by comparison, we select the best prediction model
pGM(1,1) and at the same time take coal demand factors as the
BP neural network input, 200-2015year of coal demand date for
training and testing. Lastly we proceed to predict coal demand
in China in 2016 and 2020. Prediction result is: mean relative
error of the improved tandem gray BP neural network
prediction results is 1.92%, which is lower 0.158% than pGM(1,
1) model and 0.28% than BP neural network model
Index Terms—BP neural network, gray forecast, coal demand forecast, tandem gray BP neural network.
Guohua Guo is with the Department of Modern Management, Zhengzhou Technical College, P. C. 450121 China (e-mail: firstname.lastname@example.org).
Cite: Guohua Gou, "Forecast Model of Coal Demand Based on Improved Tandem Gray BP Neural Network," International Journal of Information and Education Technology vol. 7, no. 11, pp. 870-875, 2017.