Journal of Earth system science | |
Appraisal of soft computing techniques in prediction of total bed material load in tropical rivers | |
H Md Azamathulla11  N A Zakaria11  C K Chang11  A Ab Ghani11  | |
[1] River Engineering and Urban Drainage Research Centre (REDAC), Universiti Sains Malaysia 14300 Nibong Tebal, Pulau Pinang, Malaysia.$$ | |
关键词: Alluvial channels; Sediment transport; River engineering; ANN; ANFIS; GEP.; | |
DOI : | |
学科分类:天文学(综合) | |
来源: Indian Academy of Sciences | |
【 摘 要 】
This paper evaluates the performance of three soft computing techniques, namely Gene-Expression Programming (GEP) (Zakaria et al 2010), Feed Forward Neural Networks (FFNN) (Ab Ghani et al 2011), and Adaptive Neuro-Fuzzy Inference System (ANFIS) in the prediction of total bed material load for three Malaysian rivers namely Kurau, Langat and Muda. The results of present study are very promising: FFNN (ð‘…2 = 0.958, RMSE = 0.0698), ANFIS (ð‘…2 = 0.648, RMSE = 6.654), and GEP (ð‘…2 = 0.97, RMSE = 0.057), which support the use of these intelligent techniques in the prediction of sediment loads in tropical rivers.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO201912040492293ZK.pdf | 542KB | download |