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Streamflow forecasting using least-squares support vector machines

This paper investigates the ability of a least-squares support vector machine (LSSVM) model to improve the accuracy of streamflow forecasting. Cross-validation and grid-search methods are used to automatically determine the LSSVM parameters in the forecasting process. To assess the effectiveness of...

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Bibliographic Details
Main Authors:	Shabri, Ani, Suhartono, Suhartono
Format:	Article
Language:	English
Published:	Taylor & Francis 2012
Subjects:	Q Science
Online Access:	http://eprints.utm.my/id/eprint/33550/1/AniShabri2012_StreamflowForecastingusingLeastSquares.pdf http://eprints.utm.my/id/eprint/33550/ http://dx.doi.org/10.1080/02626667.2012.714468
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