Weather Prediction Task

Weather prediction research focuses on improving the accuracy and efficiency of forecasting meteorological variables using advanced computational methods. Current efforts concentrate on refining deep learning architectures, such as convolutional neural networks (like U-Net) and recurrent neural networks (LSTMs, GRUs), often coupled with metaheuristic optimization techniques for hyperparameter tuning, to better capture complex spatio-temporal dynamics. A key challenge involves mitigating error accumulation in autoregressive models and developing robust models less susceptible to spatial-temporal shifts in data. Improved prediction accuracy has significant implications for various sectors, including agriculture, transportation, and disaster management.