An improved training algorithm of neural networks for time series forecasting

Authors:
Daiping Hu;Ruiming Wu;Dezhi Chen;Huiming Dou
Affiliations:
Antai College of Economics & Management, Shanghai Jiaotong University, Shanghai, China;Antai College of Economics & Management, Shanghai Jiaotong University, Shanghai, China;Antai College of Economics & Management, Shanghai Jiaotong University, Shanghai, China;Antai College of Economics & Management, Shanghai Jiaotong University, Shanghai, China
Venue:
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Year:
2007

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Abstract

Neural network approaches for time series forecasting, which have the property of simpleness, nonlinearity and effectiveness, have been broadly utilized in many domains. In this paper, an improved training algorithm of back-propagation neural network for time series forecasting by using dynamic learning rate in the training process is proposed. The results of some studied cases demonstrate this algorithm can increase the efficiency of neural network training and the precision of forecasts.