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...

全面介绍

Saved in:
书目详细资料
Main Authors: Shabri, Ani, Suhartono, Suhartono
格式: Article
语言:English
出版: Taylor & Francis 2012
主题:
在线阅读: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
标签: 添加标签
没有标签, 成为第一个标记此记录!