Support vector machine approach for longitudinal dispersion coefficients in natural streams

Authors:
H. Md. Azamathulla;Fu-Chun Wu
Affiliations:
REDAC, Universiti Sains Malaysia, Engineering Campus, 14300 Nibong Tebal, Pulau Pinang, Malaysia;Department of Bio-Environmental Systems Engineering, National Taiwan University, Taipei, Taiwan
Venue:
Applied Soft Computing
Year:
2011

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Abstract

This paper presents the support vector machine approach to predict the longitudinal dispersion coefficients in natural rivers. Collected published data from the literature for the dispersion coefficient for wide range of flow conditions are used for the development and testing of the proposed method. The proposed SVM approach produce satisfactory results with coefficient of determination=0.9025 and root mean square error=0.0078 compared to existing predictors for dispersion coefficient.