The objective of this study is to develop a feed forward neural network (FFNN) model and a
radial basis function neural network (RBFNN) model to predict the dissolved oxygen from …

Most of the water quality models previously developed and used in dissolved oxygen (DO)
prediction are complex. Moreover, reliable data available to develop/calibrate new DO …

The purpose of this study is to develop a feed-forward neural network (FFNN) model with
back-propagation learning algorithm to predict the dissolved oxygen from water temperature …

Water quality modeling with dynamic parameters, especially of rivers, is important in terms of
proactive pollution management strategies. Techniques such as artificial neural networks …

Water quality of the river is associated with various processes, defining its complexity in
nature. Monitoring of surface water can produce uncertain results due to spatial and …

In the present research, Artificial Neural Networks (ANNs) were developed for modelling the
performance of Al-Rustamiya wastewater treatment plant, Baghdad, Iraq. There were …