The application discloses an
arsenic concentration prediction method and device of water,
electronic equipment and storage medium, and relates to the field of
water treatment. The method comprises the following steps: acquiring the
arsenic concentration value, pH value, oxidation-
reduction potential, flow and temperature parameters of water; determining the dosing amount of
reagent according to the aforementioned parameters; taking the
arsenic concentration value of water before treatment, the dosing amount of
hypochlorite and iron salt as input samples, and taking the arsenic concentration value of water
after treatment as output samples; pre-training an error inverse feedback neural network prediction model to generate an arsenic
concentration prediction model; adjusting the size of the dosing amount of
hypochlorite and / or iron salt, combining the arsenic
concentration prediction model to obtain the predicted arsenic concentration value of water
after treatment, correcting the arsenic concentration prediction model, and optimizing the size of the dosing amount of
hypochlorite and iron salt. Through the method, the problem that current water arsenic removal relies on human experience, cannot be
fully automated, and the inaccurate dosing amount of
reagent easily leads to
reagent waste is solved.