NDLI: Application of Coupling Model with Neural Network and Projection Pursuit Based on Partial Least-Squares Regression to Water Resources Carrying Capacity Forecasting

Content Provider	IEEE Xplore Digital Library
Author	Xiao-Yong Zhao
Copyright Year	2012
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.
Starting Page	446
Ending Page	449
File Size	311872
Page Count	4
File Format	PDF
ISBN	9781467326469
DOI	10.1109/ISCID.2012.261
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Couplings Correlation Fitting partial least-squares regression coupling model with neural network and projection pursuit Predictive models Polynomials Mathematical model water resources carrying capacity Water resources
Content Type	Text
Resource Type	Article

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