Prediction of the optimal dosage of coagulants in water treatment plants through developing models based on artificial neural network fuzzy inference system (ANFIS)

• Published in: Journal of environmental health science and engineering 2021-12, Vol.19 (2), p.1543-1553
• Main Authors: Narges, Shakeri, Ghorban, Asgari, Hassan, Khotanlou, Mohammad, Khazaei
• Format: Article
• Language: English
• Subjects: Alkalinity; Artificial neural networks; Clustering; Coagulants; Coagulation; Correlation coefficient; Correlation coefficients; Earth and Environmental Science; Electrical conductivity; Electrical resistivity; Environment; Environmental Economics; Environmental Engineering/Biotechnology; Environmental Health; Environmental Law/Policy/Ecojustice; Error analysis; Flocculation; Fuzzy logic; Human error; Jar tests; Neural networks; Quality of Life Research; Raw water; Research Article; Turbidity; Waste Management/Waste Technology; Water quality; Water treatment; Water treatment plants
• ISSN: 2052-336X; 2052-336X
• DOI: 10.1007/s40201-021-00710-0

Purpose Coagulation and flocculation are the prominent processes and unit-operations in water treatment plants. One of the most challenging operations in water treatment process is determining of the coagulant dose. Method The Jar-test method is usually used to determine the coagulant dose. Considering that this traditional method is time consuming, associated with human error and highly affected by raw water quality fluctuations. In this study, artificial fuzzy neural network (ANFIS) according to subtractive clustering (SUB) method was applied in order to determine the optimal dose of coagulant in the water treatment plants. Results Adopting SUB method tend to moderate the number of rules and the interconnections besides enhancing the model responsibility and smart model recognition. The amount of pH, turbidity of raw water influent, alkalinity, temperature, and electrical conductivity were collected as input data. Conclusions The results of modeling by ANFIS with correlation coefficients of 0.85 and 0.84 and RMSE 1.32 and 1.83, respectively, for alum and polyaluminum chloride (PAC) coagulant dose, indicated that ANFIS is an effective method for determination of the optimal coagulation dose in the water treatment plant.