Modeling River Stream Flow Using Support Vector Machine

Support Vector Machine (SVM) is a new tool from Artificial Intelligence (AI) field has been successfully applied for a wide variety of problem especially in river stream flow forecasting. In this paper, SVM is proposed for river stream flow forecasting. To assess the effectiveness SVM, we used month...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 315; pp. 602 - 605
Main Authors Rafidah, Ali, Suhaila, Yacob
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.04.2013
Subjects
Support Vector Machine (SVM)
Artificial Intelligence (AI)
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Summary:Support Vector Machine (SVM) is a new tool from Artificial Intelligence (AI) field has been successfully applied for a wide variety of problem especially in river stream flow forecasting. In this paper, SVM is proposed for river stream flow forecasting. To assess the effectiveness SVM, we used monthly mean river stream flow record data from Pahang River at Lubok Paku, Pahang. The performance of the SVM model is compared with the statistical Autoregressive Integrated Moving Average (ARIMA) and the result showed that the SVM model performs better than the ARIMA models to forecast river stream flow Pahang River.
Bibliography:Selected, peer reviewed papers from the 3rd International Conference on Mechanical & Manufacturing Engineering 2012, November 20–21, 2012, Malaysia
ISBN:9783037856352
3037856351
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.315.602