Evaluation the turbidity removal efficiency in Al-Wahda water treatment plant using statistical indicators

Most of drinking water consuming all over the world has been treated at treatment plant (WTP) where raw is abstracted from reservoirs and rivers. The turbidity removal efficiency very important to supply safe water. This study focusing on use multiple linear regression (MLR) artificial neural network (ANN) models predict Al-Wahda WTP in Baghdad city. measured physico-chemical parameters were used determine their effect various processes. suitable formulation ANN model examined throughout many preparations, trials, steps evaluation. prediction are presented. Results found that estimating by MLR could be successful. Moreover, results showed influent effluent concentration have more predicting other parameters. Finally, accurate than according coefficient correlation (0.925).