Floods are among the most destructive natural disasters, which are highly complex to model.
The research on the advancement of flood prediction models contributed to risk reduction …

Since the middle of the twentieth century, artificial intelligence (AI) models have been used
widely in engineering and science problems. Water resource variable modeling and …

Selecting an adequate set of inputs is a critical step for successful data-driven streamflow
prediction. In this study, we present a novel approach for Input Variable Selection (IVS) that …

This paper examined the efficiency of multivariate linear regression (MLR) and artificial
neural network (ANN) models in prediction of two major water quality parameters in a …

This paper traces two decades of neural network rainfall-runoff and streamflow modelling,
collectively termed 'river forecasting'. The field is now firmly established and the research …

With the great development of e-commerce, users can create and publish a wealth of
product information through electronic communities. It is difficult, however, for manufacturers …

Water | Free Full-Text | Flood Stage Forecasting Using Machine-Learning Methods: A Case
Study on the Parma River (Italy) Next Article in Journal An Empirical Seasonal Rainfall …

This paper proposes a hybrid intelligent model for runoff prediction. The proposed model is
a combination of data preprocessing methods, genetic algorithms and levenberg–marquardt …

The conventional ways of constructing artificial neural network (ANN) for a problem
generally presume a specific architecture and do not automatically discover network …

Measurement of evaporation (E) rate from various natural surfaces is known as the key
element in any hydrological cycle and hydrometeorological studies. Due to the shortage of …