DocumentCode :
588938
Title :
Application of Coupling Model with Neural Network and Projection Pursuit Based on Partial Least-Squares Regression to Water Resources Carrying Capacity Forecasting
Author :
Xiao-Yong Zhao
Author_Institution :
Coll. of Hydrol. & Water Resources, Hohai Univ., Nanjing, China
Volume :
2
fYear :
2012
fDate :
28-29 Oct. 2012
Firstpage :
446
Lastpage :
449
Abstract :
The method of partial least-squares regression can effectively deal with the problems of multicollinearity among independent variables", "but can not ideally solve the complicated problems of nonlinearity between dependent variables and independent variables. The method of coupling model with neural network and projection pursuit is an ideal tool to deal with the problem of nonlinearity, and it is very steady, but can not ideally solve the problems of multicollinearity among independent variables. The paper combines the two methods to establish the method of coupling model with neural network and projection pursuit based on partial least-squares regression for forecast water resources carrying capacity. the results of forecasting indicate that the combination is superior to either of them, the model was found to be able to give satisfactory effect.
Keywords :
forecasting theory; least squares approximations; neural nets; regression analysis; water resources; carrying capacity forecasting; coupling model; forecast water resources carrying capacity; independent variables; neural network; partial least-squares regression; projection pursuit; Correlation; Couplings; Fitting; Mathematical model; Polynomials; Predictive models; Water resources; coupling model with neural network and projection pursuit; partial least-squares regression; water resources carrying capacity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2646-9
Type :
conf
DOI :
10.1109/ISCID.2012.261
Filename :
6406034
Link To Document :
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