Suspended sediment is a natural part of river systems and plays an essential role in
structuring the landscape, creating ecological habitats and transporting nutrients. It is also a …

An accurate model for sediment prediction is a priority for all hydrological researchers. Many
conventional methods have shown an inability to achieve an accurate prediction of …

This paper investigates the abilities of Artificial Neural Networks (ANN), Least Squares–
Support Vector Regression (LS-SVR), Fuzzy Logic, and Adaptive Neuro-Fuzzy Inference …

Rainfall-runoff process was modeled for a small catchment in Turkey, using 4 years (1987–
1991) of measurements of independent variables of rainfall and runoff values. The models …

In recent decades, development of artificial intelligence, as a predictor for hydrological
phenomenon, has created a great change in predictions. This paper investigates the …

Accurate and reliable suspended sediment load (SSL) prediction models are necessary for
planning and management of water resource structures. More recently, soft computing …

Evaporation rate is one of the key parameters in determining the ecological conditions and it
has an irrefutable role in the proper management of water resources. In this paper, the …

In order to improve the real time forecasting of foods, this paper proposes a modified Takagi
Sugeno (T–S) fuzzy inference system termed as threshold subtractive clustering based …

A new conjunction method (wavelet-neuro-fuzzy) for precipitation forecast is proposed in this
study. The conjunction method combines two methods, discrete wavelet transform and …

Ensemble machine learning models have been widely used in hydro-systems modeling as
robust prediction tools that combine multiple decision trees. In this study, three newly …