A Machine Learning-Based Predictive System for Marine Operability Forecasting

This work presents a probabilistic machine learning framework for marine operability forecasting aimed at supporting offshore operational planning under uncertainty. The approach combines numerical weather prediction outputs from the ECMWF Integrated Forecasting System with high-resolution in situ measurements from EOLOS Floating LiDAR buoys.