This repository contains the code for an Ocean Front Prediction Model, designed to predict the occurrence and movement of ocean fronts using oceanographic data and machine learning techniques. The model leverages historical data, satellite imagery, and oceanographic parameters to make accurate predictions that are vital for understanding marine ecosystems and supporting navigation and fisheries management.

Dataset: Bohai sst dataset, kuroshio sst dataset, Bohai ocean front dataset, kuroshio ocean front dataset

Evaluation Method: F_Score

Comparison Method：CNN， LSTM， ConvLSTM, GAT, CFCC-LSTM

Before running the code, ensure you have the following dependencies installed:
Python 3.x
NumPy
Scipy
Scikit-learn
Kreas
TensorFlow or PyTorch (depending on the model architecture)
Matplotlib (for map visualizations)
Math (for handling mathmatic computation)