Modeling River Stream Flow Using Support Vector Machine

Ali Rafidah; Yacob Suhaila

doi:10.4028/www.scientific.net/AMM.315.602

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 315Modeling River Stream Flow Using Support Vector...

Modeling River Stream Flow Using Support Vector Machine

Abstract:

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.

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Periodical:

Applied Mechanics and Materials (Volume 315)

Pages:

602-605

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.315.602

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Online since:

April 2013

Authors:

Ali Rafidah, Yacob Suhaila

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Artificial Intelligence (AI), Support Vector Machine (SVM)

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