Investigating the Prediction of the Amount of Coagulant Injection in the Drinking Water Purification Process Using Fuzzy Regression Analysis (Case Study: Mashhad Water Treatment Plant No.3)

Abstract

Surface waters have various impurities. Aggregation of particles and their transformation from dispersed and fine states to coarse state is done by a process called coagulation process. This process is one of the basic processes in drinking water treatment plants. The purpose of this research is to provide a suitable relationship for determining the amount of chlorophric coagulant injection in the coagulation and flocculation process using fuzzy regression in drinking water treatment plant No. 3 of Mashhad. Temperature, pH, turbidity, electrical conductivity and TDS of raw and purified water have been used as primary data to determine the appropriate equation to predict the amount of coagulant injection in the purification process. Appropriate coefficients for different linear, power, exponential and quadratic models were determined in two types of least squares and regression. According to the results obtained in this research, the exponential-regression model with RMSE equal to 0.68. It has been introduced as a desirable model.

Keywords

• fuzzy regression
• coagulant
• drinking water
• coagulation