Space-time multi-source offshore water quality time sequence prediction method of LSTM coupling mechanism model

The invention relates to the technical field of data prediction, in particular to a time-space multi-source offshore water quality time sequence prediction method of an LSTM coupling mechanism model, which comprises the following steps: collecting water area monitoring data and preprocessing; carrying out pollution source accounting based on the monitoring data; building a new LSTM network time sequence water quality prediction model of a double-stage attention weight optimization mechanism based on a water quality time sequence prediction machine learning algorithm basic library, and fusing the new LSTM network time sequence water quality prediction model with a graph convolutional neural network; a three-dimensional tidal current dynamic model is built based on the fusion algorithm, and time sequence prediction of the offshore water quality is achieved. According to the invention, an LSTM network time sequence water quality prediction new model of a double-stage attention weight optimization mechanism is ad