doi: 10.18178/ijiet.2017.7.11.987
Forecast Model of Coal Demand Based on Improved Tandem Gray BP Neural Network
Guohua Gou
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 respectively.
Keywords
- BP neural network
- gray forecast
- coal demand forecast
- tandem gray BP neural network
How to 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. https://doi.org/10.18178/ijiet.2017.7.11.987
Copyright & License
Copyright © 2017 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).