Title :
A Novel Approach for Time Series Analysis Based RBF Neural Network
Author :
Zou, Kaiqi ; Dong, Renfei
Author_Institution :
Coll. of Inf. Eng., Univ. Key Lab. of Inf. Sci. & Eng., Dalian, China
Abstract :
In this paper, we analyzed the highly nonlinear characteristics of the stock market and proposed a novel approach for time series analysis. This method is the use of RBF neural network analysis of time series and analysis of the initial analysis of the error also, and then combined with the analysis of two results to obtain new results. Using this method, we forecasted the trend of shares of China Unicom and achieved satisfactory results.
Keywords :
forecasting theory; radial basis function networks; stock markets; time series; China Unicom; RBF neural network analysis; error analysis; stock market; time series analysis; Analytical models; Artificial neural networks; Biological neural networks; Predictive models; Radial basis function networks; Stock markets; Time series analysis; RBF; nonlinear; stock market; time series analysis;
Conference_Titel :
Information Technology and Applications (IFITA), 2010 International Forum on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-7621-3
Electronic_ISBN :
978-1-4244-7622-0
DOI :
10.1109/IFITA.2010.37
