A Genetic Ensemble Method for Correcting Maritime Wind Forecasts

Maritime accidents can cause significant damage to both human life and the environment. To respond quickly and effectively, accurate wind prediction is crucial. This study focuses on optimizing the weights of an ensemble voting model for wind data prediction using genetic algorithms (GAs). The GA-based approach significantly improved wind prediction accuracy by optimizing the weights of various models. Data from seven observation stations near South Korea was used, and the GA-based model outperformed the ECMWF High-Resolution model, achieving a 24.6% improvement in RMSE. This highlights the potential of GA in wind prediction models and its significant application in maritime accident response systems.