Water Quantity Prediction Using Least Squares Support Vector Machines (LS-SVM) Method

Water Quantity Prediction Using Least Squares Support Vector Machines (LS-SVM) Method

The impact of reliable estimation of stream flows at highly urbanized areas and the associated receiving waters is very important for water resources analysis and design. We used the least squares support vector machine (LS-SVM) based algorithm to forecast the future streamflow discharge. A Gaussian...

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Bibliographic Details
Main Authors:	Nian Zhang, Charles Williams, Pradeep Behera
Format:	Article
Language:	English
Published:	International Institute of Informatics and Cybernetics 2014-08-01
Series:	Journal of Systemics, Cybernetics and Informatics
Subjects:	Least Squares Support vector Machine Water Quantity Prediction
Online Access:	http://www.iiisci.org/Journal/CV$/sci/pdfs/SA145GH14.pdf

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