Streamflow forecasting using least-squares support vector machines

• 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

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...