Modelling coagulant dose with an adaptive neuro-fuzzy inference system (anfis) Application to water treatment plant of Boudouaou (Algeria)
Coagulation is an important component of water treatment. Determining the optimal coagulant dosage is vital, as insufficient dosage will result in undesirable treated water quality. A number of chemicals have been used successfully in coagulation, particularly alum (Al2SO4•18H2O). Traditionally, jar tests are used to determine the optimum coagulant dose. However, this is expensive and time-consuming and does not enable responses to changes in raw water quality in real time. An optimal modeling approach can be used to overcome these limitations. The main purpose of this study was to investigate the applicability and capability of Adaptive-Network-Based Fuzzy Inference System (ANFIS) and Neural Network (ANN) methods for modeling coagulant dose. To verify the application of this approach, Boudouaou surface water, located in the northern part of Algeria, was chosen as the case study area. The data used for the determination of the models included six (6) input variables describing the raw water characteristics (temperature, pH, turbidity, conductivity, dissolved oxygen and the ultraviolet absorption). The data set was divided into two (2) subgroups, calibration and validation periods. Coagulant models having various input structures were trained and tested to investigate the applicability of the used methods. To obtain a more accurate evaluation of the results for the ANFIS models, the best fit model structures were also tested by artificial neural network (ANN) and multiple linear regression (MLR) methods. The results of three methods were compared, and it was observed that the ANFIS is preferable and can be applied successfully because it provides high accuracy and reliability for coagulant dosage modelling, according to the following performance evaluation criteria: determination coefficient (R2), Root Mean Square Error (RMSE) and bias (B). The results are of practical importance: the coagulant dose changes according to the six variables representing the raw water characteristics, as there is no one dominant variable.