Ocean front prediction method based on space-time coupling

Abstract

The application discloses a kind of ocean front prediction methods based on space-time coupling, belong to the cross technical field of ocean science and deep learning.The method includes: spatial feature extraction module utilizes cross-shaped window attention mechanism and local enhancement position coding, capture long-range spatial dependence and multi-scale structure features existing in ocean front;Time series modeling module through double memory state and adaptive gating mechanism, respectively memory ocean front short-term dynamic change and background field long-term evolution trend;Space-time feature fusion module realizes the weighted fusion of spatial and temporal features with the help of cross attention mechanism;Multi-component loss function optimizes the prediction effect from the dimensions of numerical accuracy, gradient characteristics, morphological structure, etc.The application solves the space-time coupling modeling problem caused by multi-scale interaction, nonlinear dynamics effect of ocean front through the strategy of predicting interdiurnal change amount + recursive superposition and multi-module collaborative mechanism, realizes the accurate prediction of ocean front under complex environment.