Title :
The Application of Improved Elman Neural Network in the Exchange Rate Time Series
Author_Institution :
Coll. of Economic, Jiaxing Univ., Jiaxing, China
Abstract :
In this paper, we select the Elman neural network method to improve because of its good non-linear effect of disturbance elimination, and present a new exchange rate time series prediction method. We point out a new improved Elman neural network model firstly, and then predict the time series of RMB exchange rate against U. S. dollar. Through the forecasting process, we determine the input variables for the network structure, and determine the neural network´s critical parameters to forecasting. The results show that the improved Elman network can obtain better results during the forecasting process.
Keywords :
exchange rates; neural nets; time series; RMB exchange rate; U. S. dollar; exchange rate time series prediction method; improved Elman neural network method; neural network critical parameters; Artificial neural networks; Biological system modeling; Exchange rates; Forecasting; Mathematical model; Neurons; Predictive models; exchange rate forecasting; improved Elman network; time series analysis;
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
DOI :
10.1109/AICI.2010.330