Journal
JOURNAL OF EARTH SYSTEM SCIENCE
Volume 121, Issue 1, Pages 125-133Publisher
INDIAN ACAD SCIENCES
DOI: 10.1007/s12040-012-0138-1
Keywords
Alluvial channels; Sediment transport; River engineering; ANN; ANFIS; GEP
Funding
- Department of Irrigation and Drainage Malaysia [JPS(PP)/SG/05/07]
- Universiti Sains Malaysia [PRE .1001/PREDAC/811077]
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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 (R-2 = 0.958, RMSE = 0.0698), ANFIS (R-2 = 0.648, RMSE = 6.654), and GEP (R-2 = 0.97, RMSE = 0.057), which support the use of these intelligent techniques in the prediction of sediment loads in tropical rivers.
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