A decision support system for coagulation and flocculation processes using the adaptive neuro-fuzzy inference system

Decision support system (DSS) is an approach to have a smart and sustainable management of facilities for monitoring, predicting controlling sections. The mentioned platform can be useful in operation complex like the water treatment plant (WTP). This study proposes adaptive neuro-fuzzy inference (ANFIS) prediction energy consumption outlet turbidity according inlet ferric chloride as coagulant coagulation flocculation unit process WTP. outcomes ANFIS model are used Petri Net modeling conceptual control system. Therefore, main purpose this research development DSS processes results quantitative data analysis showed that correlation coefficients more than 80% meaning it reliably predict consumption’s variables. With regards our findings, first one provide implemented operations WTPs. It goes without saying that, confirms variation 15 ± 5% values additive materials (ferric chloride) should set, on 60–85 40–60 kg/day, respectively, turbidity. At last but not least, benefit from manage WTP with high efficiency low human-based errors.