Neural Network with Partial Least Square Prediction Model Based on SSA - MGF

Author

YouJun Zhou ; JianSheng Wu ; FaJin Qin

Author_Institution

Dept. of Math. & Comput., Liuzhou Teacher Coll.

Volume

1

fYear

2006

fDate

21-23 June 2006

Firstpage

2777

Lastpage

2782

Abstract

The primitive rainfall series be reconstructed and become as independent variables by singular spectrum analysis and mean generating function, so primitive rainfall series be as dependent variables. The factor affecting be withdrew by means of partial least squares method to extract the most important components so that it can be input as the neural network, and established the forecast model of the neural network with least squares regression based singular spectrum analysis and mean generating function, results show that the model is superior in predictions compared to the other models, and it is a useful model for the actual operational forecasting

Keywords

geophysics computing; least squares approximations; neural nets; rain; regression analysis; spectral analysis; weather forecasting; forecast model; mean generating function; neural network; operational forecasting; partial least square prediction model; partial least squares regression; rainfall series reconstruction; singular spectrum analysis; Computer networks; Educational institutions; Electronic mail; Independent component analysis; Intelligent control; Least squares methods; Mathematical model; Mathematics; Neural networks; Predictive models; Mean Generating Function; Neural Network; Partial Least Squares Regression; Singular Spectrum Analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712870

Filename

1712870