A master’s thesis at the College of Engineering at the University of Basrah discussed (the use of an artificial neural network with a genetic algorithm and an annealing simulation algorithm to model water pollution in the city of Basrah)
The thesis presented by the student Iman Ali Abdul Karim dealt with two methods of modeling, which are the multiple linear regression (MLR) method.
The method of artificial neural network (ANN), annealing simulation (SA) technique and algorithm technique were followed. 
The artificial neural network method was combined with annealing simulation (ANN-SA) technique and the
Artificial Neural Network with Genetic Algorithm (ANN-GA) method to perform best value estimation
independent variables which reduce the value of water quality indicators and water pollution.
The thesis aims to assess the water quality of the Shatt Al-Arab using the Water Pollution Index (WPI) and the Comprehensive Pollution Index (CPI).
And the Water Quality Index (WQI) for drinking and irrigation water in fifteen water treatment plants for a period of ten years
The thesis concluded that both the artificial neural network method combined with annealing simulation technique and the network method
Artificial neural technology combined with genetic algorithm technology to give the lowest value for quality index
Water quality index (WQI) at the optimum variables with regard to irrigation water, as it reached the minimum value of the water quality index
For irrigation water (41.5661).