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Using Meta-heuristic Models for Simulation of Sediment Transport in Rivers

p. 97-108

Abstract

Two important characteristics of the hydrologic phenomena are their non-linear behaviour and uncertainty and ambiguity in their nature. So, as a hydrologic phenomenon, the sediment transport possesses a kind of uncertainty and ambiguity as well. Recently, use of Artificial Neural Networks (ANNs) and fuzzy sets in simulation and modelling of the systems with uncertainty bas produced suitable results. In this research, for modelling and prediction of sediment transport of river flows, the Adaptive Neuro-Fuzzy Inference System (ANFIS) as a method based on the ANNs and fuzzy sets was used. Using several ANNs and ANFIS models for prediction of sediment load transport showed that using the river discharge in the current period and the river discharge and the sediment load in the previous period as the models nodes, yields the best results.

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References

Bibliographical reference

Saeed Alimohammadi and Ebrahim Jabbari, « Using Meta-heuristic Models for Simulation of Sediment Transport in Rivers », CASYS, 19 | 2006, 97-108.

Electronic reference

Saeed Alimohammadi and Ebrahim Jabbari, « Using Meta-heuristic Models for Simulation of Sediment Transport in Rivers », CASYS [Online], 19 | 2006, Online since 22 August 2024, connection on 27 December 2024. URL : http://popups.uliege.be/3041-539x/index.php?id=2469

Authors

Saeed Alimohammadi

Civil Engineering College

Iran University of Science and Technology, Tehran, Iran

Ebrahim Jabbari

Civil Engineering College

Iran University of Science and Technology, Tehran, Iran

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Copyright

CC BY-SA 4.0 Deed