The use of Artificial Neural Networks in the modeling of socioeconomic category of Integrated Water Resources Management (Case study: Saf-Saf River Basin, North East of Algeria)

Application of mapping and statistical study for the assessment of surface water quality in the Safsaf River (North-Eastern Algeria)

“…The Safsaf watershed receives discharges from the industrial area of the city of Skikda, where there is a petrochemical complex, as well as inputs from urban domestic water (Kaddeche et al, 2022). The industry is mainly located downstream of the Safsaf River basin, where it consumes about 7.1 million cubic meters of water per year (Sakaa et al, 2013).…”

Predicting water allocation trade prices using a hybrid Artificial Neural Network-Bayesian modelling approach

“…Typically, water resource researchers have used conventional modelling techniques such as regression analysis, time series analysis and autoregressive moving averages (Jain et al, 2001). More recently, due to the inherent complexity in modelling water resources, the nonlinearity of water allocations, and the difficulties of building linear relationships between water allocations for winter and summer periods using conventional models, researchers have adopted the artificial neural network (ANN) method to estimate these complex factors (Khan et al, 2005;Kingston et al, 2005;Maier et al, 2010;Sakaa et al, 2013;Liu et al, 2014;Li et al, 2015;Wu et al, 2014). ANN models emulate the properties of biological nervous systems for adaptive learning from historical data, using patterns in the data to predict the future (Nowlan and Hinton, 1992;Cancelliere et al, 2002).…”