A hybrid method for forecasting river-suspended sediments in Iran

• Published in: International journal of river basin management Vol. 15; no. 4; pp. 453 - 460
• Main Authors: Tavakoli Targhi, Alireza, Abbaszadeh, Sadegh, Arabasadi, Zeinab
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 02.10.2017; Taylor & Francis Ltd
• Subjects: artificial neural network; Artificial neural networks; Correlation coefficient; Correlation coefficients; cuckoo optimization algorithm; discharge; Fluvial sediments; Forecasting; Hydrology; Learning algorithms; Mathematical models; Methods; Neural networks; Optimization; Rivers; Sediment; Sediment discharge; Sediments; Suspended sediments

Estimation of sediment mass carried by rivers is an important issue in Hydrological Sciences. The main purpose of this research was to find an appropriate method to compute sediment discharge. Some machine-learning approaches have been used to forecast river-suspended sediments, correctly. One of th...