A prediction of the wastewater treatment plant
(WWTP) using a genetic algorithm based on historical
data. In Iran, the majority of treated wastewater is used
in agriculture.As a result, using waste water with poor
quality attributes might be hazardous to one's health. The
effectiveness of the neuralnetwork model in predicting
performance was investigated in this study. To find
relationships in the data, exploratory data analysis was
employed and evaluated at a dependency level. The neural
network models' proper architecture was identified
through a series of training and testing stages. The ANNbased models were discovered to be a useful and reliable
tool for predicting WWTP performance. The activated
sludge methodwill be considered as a replacement for the
semi-mechanical treatment system.
Wastewater, ANN, Neuralnetwork, Geneticalgorithm.