Prioritising construction accident risk factors using an integrated Random Forest, XGBoost, and ANN framework with sensitivity analysis
Construction safety remains a critical concern due to accidents influenced by multiple interacting factors. While previous studies have identified key risk drivers, robust, data-driven approaches for prioritising them remain limited. This study proposes an integrated machine learning and sensitivity-based framework to...