Prediction of Surface Water Supply Sources for the District of Columbia Using Least Squares Support Vector Machines (LS-SVM) Method

Journal: Advances in Computer Science : an International Journal(ACSIJ) (Vol.4, No. 1)

Publication Date: 2015-01-31

Authors : Nian Zhang; Roussel Kamaha; Pradeep Behera;

Page : 1-9

Keywords : Water Quantity Prediction; Least Squares Support vector Machine;

Source : Download Find it from : Google Scholar

Abstract

In this research, we developed a predictive model based on least squares support vector machine (LS-SVM) that forecasts the future streamflow discharge using the past streamflow discharge data. A Gaussian Radial Basis Function (RBF) kernel framework was b ...

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Prediction of Surface Water Supply Sources for the District of Columbia Using Least Squares Support Vector Machines (LS-SVM) Method

Abstract

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