The invention relates to a measurement parameter prediction and
sewage treatment control method based on
deep learning. The method comprises the following steps: step 1, acquiring real-time
sewage treatment online instrument measurement
time sequence data; step 2, performing data cleaning and
wavelet transform on the
time series data to obtain high-frequency components of each level; step 3, respectively
processing the high-frequency components of each level, inputting the processed high-frequency components into the trained GRU neural
network model, and outputting prediction results corresponding to the high-frequency components of each level; step 4,
processing the prediction results corresponding to the high-frequency components of all the levels again and then combining the results towavelet reconstruction to acquire measurement parameters subjected to prediction; and step 5, performing corresponding control action on the corresponding control link of the
sewage treatment according to the measurement parameters subjected to the prediction treatment. Compared with the prior art, the invention has the advantages that parameters can be relatively accurately estimated in advance,control
lag is avoided, meanwhile, the
measurement frequency can be reduced, and the cost is reduced.