Application of soft-computing techniques in forecasting sediment load and concentration
Author:
Affiliation:
1. Department of Civil and Environmental Engineering, Amirkabir University of Technology, Tehran, Iran
2. Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, Canada
Publisher
Informa UK Limited
Subject
Water Science and Technology
Link
https://www.tandfonline.com/doi/pdf/10.1080/02626667.2020.1790565
Reference67 articles.
1. Prediction of suspended sediment load using ANN GA conjunction model with Markov chain approach at flood conditions
2. Forecasting of Runoff and Sediment Yield Using Artificial Neural Networks
3. Suspended sediment load simulation by two artificial neural network methods using hydrometeorological data
4. Cross validation and MLP architecture selection
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4. MODWT—random vector functional link for river-suspended sediment load prediction;Arabian Journal of Geosciences;2022-05
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