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 (Author), Suhartono, Suhartono (Author)
Format: Article
Language:English
Published: Taylor & Francis, 2012-08.
Subjects:
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