%0 Journal Article
%T Thermal Power Industry NOX Emissions Forecast Based on Improved Tandem Gray BP Neural Network
%A Jianguo Zhou
%A Lin Meng
%A Xiaodan Pan
%J Research Journal of Applied Sciences, Engineering and Technology
%D 2013
%I Maxwell Science Publication
%X In this study, we build a new thermal power sector NOx emissions prediction model of tandem gray BP neural network. Firstly we use 1994-2010 years NOx emissions 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 NOx emissions factors as the BP neural network input, 1994-2010 year of NOx emissions data for training and testing. Lastly we proceed to predict thermal power industry NOx emissions in China in 2013 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.
%K BP neural network
%K grey forecast
%K NOx emissions forecast
%K tandem gray BP neural network
%U http://www.maxwellsci.com/jp/abstract.php?jid=RJASET&no=300&abs=18