A medium and long term runoff intelligent prediction method

Abstract

This invention relates to the field of hydrological forecasting technology and discloses a medium- and long-term intelligent runoff forecasting method, comprising: collecting watershed data, preprocessing and extracting features, generating a feature vector sequence and dividing it into training sets; constructing a physical constraint recurrent neural network module and training it based on the total loss function of physical constraint loss; constructing a sliding window online adaptive correction module, initializing the sliding window to store the measured runoff values ​​and preliminary runoff forecast values ​​of the most recent O times; inputting the feature vector of the current time into the trained physical constraint recurrent neural network module to generate preliminary runoff forecast values, calculating the historical average deviation according to the window state and correcting it to obtain the final forecast result; finally, forming a new sample pair of measured runoff values ​​and preliminary runoff forecast values ​​and adding it to the window while removing the oldest sample to achieve dynamic window updates; this invention achieves high-precision, high-physical-consistency, and online adaptive intelligent forecasting of medium- and long-term runoff.

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