Title :
Forecasting the Price of Online Auction Items Based on a Hybrid Approach of ANN and GRA
Author_Institution :
Sch. of Inf. Technol., Jiangxi Univ. of Finance & Econ., Nanchang, China
Abstract :
Aiming at the BP artificial neural network unable to auto select and optimize input variables, this paper integrates BPANN with grey relational analysis method, establishes an optimized BP artificial neural network arithmetic (GM2BPANN) which based on the grey relational analysis method. The hybrid approach has been used to forecasting the online item price. The result shows that the new model can deal with mass input variables without special subjective selection, enhances the adapt ability of BP neural network. It can also get good forecasting stability and accuracy.
Keywords :
backpropagation; electronic commerce; grey systems; neural nets; pricing; BP artificial neural network arithmetic; backpropagation; grey relational analysis; online auction item; online item price forecasting; Adaptation model; Artificial neural networks; Forecasting; Mathematical model; Neurons; Predictive models; Training;
Conference_Titel :
Management and Service Science (MASS), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5325-2
Electronic_ISBN :
978-1-4244-5326-9
DOI :
10.1109/ICMSS.2010.5576549