Self-learning sewage plant water inflow prediction method based on Fourier transform

The invention belongs to the field of sewage plant water inflow prediction, and discloses a self-learning sewage plant water inflow prediction method based on Fourier transform. The method comprises the following steps of performing collection, timestamp data conversion, cleaning and remaining data storage on inflow historical data to obtain an original data set; building a preliminary Fourier transform prediction model by using the original data set, and obtaining original predicted water inflow data of each time node within the prediction time; determining the correction period duration in the prediction time; and performing self-learning correction on the original predicted water inflow data in the next correction period by using the original predicted water inflow data of each time node in the previous correction period and the corresponding actually measured water inflow data, obtaining the corrected predicted water inflow data in the next correction period, and storing the corrected predicted water infl