Suspended sediment load estimate using support vector machines in Kaoping river basin

Strong correlation exists between river discharge and suspended sediment load. The relationship was used to estimate suspended sediment load by using linear regression model, power regression model, artificial neural network and support vector machine in this study. Records of river discharges and s...

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Bibliographic Details
Main Authors: Jie-Lun Chiang, Yu-Shiue Tsai
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Back-propagation network
Biological system modeling
Kernel
Load modeling
river discharge
Rivers
Sediments
support vector machine
Support vector machines
suspended load
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Summary:Strong correlation exists between river discharge and suspended sediment load. The relationship was used to estimate suspended sediment load by using linear regression model, power regression model, artificial neural network and support vector machine in this study. Records of river discharges and suspended sediment loads in Kaoping river basin were investigated as case study. Eighty-five percent of the records were used as training data set to develop those four models. The other fifteen percent records were used as verification data set. The performance of the four models was evaluated by root mean square errors (RMSE). The RMSEs show: support vector machine
DOI:10.1109/CECNET.2011.5769267