DocumentCode
690347
Title
Prediction of Market Demand Based on AdaBoost_BP Neural Network
Author
Song Li ; Jing Wang ; Bo Liu
Author_Institution
Sch. of Manage., Hebei Univ., Baoding, China
fYear
2013
fDate
14-15 Dec. 2013
Firstpage
305
Lastpage
308
Abstract
Aiming at the disadvantages of prediction model of single BP neural network, a prediction model was presented by combining AdaBoost algorithm and BP neural network for improving the forecasting accuracy of single BP neural network. The ensemble BP network based on AdaBoost is used as intelligent algorithm. Overcoming the instability of single BP neural network, the proposed models can give more accurate and stable prediction for the novel conditions. The main influence factors for prediction of market demand of refrigerator are analyzing detailed and used as the inputs of proposed prediction model. The efficiency of the proposed prediction model was tested by simulation of the market demand statistical data of a refrigerator enterprise in China. The simulation results have shown that the higher accuracy is expressed in this proposed model, and it is applicable to practice.
Keywords
backpropagation; digital simulation; marketing; neural nets; refrigerators; statistical analysis; AdaBoost_BP neural network; ensemble BP network; intelligent algorithm; market demand statistical data simulation; refrigerator market demand prediction; single BP neural network; Accuracy; Biological neural networks; Forecasting; Prediction algorithms; Predictive models; Training; AdaBoost algorithm; BP neural networ; prediction of market demand;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Sciences and Applications (CSA), 2013 International Conference on
Conference_Location
Wuhan
Type
conf
DOI
10.1109/CSA.2013.77
Filename
6835604
Link To Document