Application of ANFIS for coagulant dosing process in a water purification plant

It is very important to optimize the turbidity of the treated water by dosing coagulant in water purification plant. The coagulant reaction to the turbidity is, however, not yet to be clarified and the amount of coagulant can not be easily calculated. In this work an adaptive network-based fuzzy inference system (ANFIS) based on conditional fuzzy c-means is employed to model the coagulant reaction to the turbidity of the treated water and the historical jar-test data are used to train the ANFIS. From this, we obtained a better performance than previous works using neural network and finally validated its efficiency by a set of real field data.