The invention discloses an electro-
catalysis treatment method for removing
uranium-containing
wastewater, and relates to the technical field of electro-
catalysis, according to the electro-
catalysis treatment method, an embedded sensor network is used for collecting data such as concentration,
conductivity and pH value of
uranyl ions U (VI) and coexisting
metal ions in
wastewater in real time,
time sequence data are corrected through DTW, and time dimension inconsistency deviation is eliminated; based on the preprocessed data, a
deep learning model combining a
convolutional neural network CNN and a
recurrent neural network RNN is constructed, the CNN is used for extracting spatial characteristics of
ion concentration distribution, the RNN captures time dependence characteristics of dynamic changes of ions, an attention mechanism is introduced to focus key interference ions, and a
characteristic matrix for priority
processing is generated; according to the method, the electrocatalysis operation parameters are further optimized through the interference
ion characteristics output by
model prediction and the dynamic influence of the interference
ion characteristics on U (VI)
selective adsorption, so that the adsorption efficiency and
energy consumption are balanced, and meanwhile,
global optimization is performed in combination with a comprehensive objective function, so that the adsorption efficiency of
uranyl ions is optimal.