Abstract
In order to make more accurate and scientific predictions of the industrial economy, we integrated the method of BP artificial neural network with grey relational analysis method together as an Industrial economic forecasting model in this study, and applied it to predict the gross industrial output of Huainan City in China. This paper examines two most recent patents between May 2012 and January 2013 in the area of forecasting. The efficiency and effectiveness of the new model is tested by comparing the predicted results with stepwise regression and GM (1, 1) models. The empirical results indicated that the new integrated model can improve the adaptability of the forecasting method and it also showed good forecasting stability and accuracy.
Keywords: BP neural network, China, grey forecast, grey relational analysis, industrial economic forecast.
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