Research on Gas Hazard Level Prediction in Coal Mines Based on Improved Sparrow Search Algorithm

Gas hazard prediction is crucial for ensuring safety in coal mining operations. This study proposes an improved Sparrow Search Algorithm (ISSA) to enhance the accuracy and efficiency of gas hazard level predictions. The traditional Sparrow Search Algorithm is augmented with adaptive mechanisms and chaotic perturbations to prevent premature convergence and improve global optimization capability. The improved algorithm is integrated with a predictive model, leveraging real-world gas monitoring data. Comparative experiments demonstrate that the ISSA-based prediction model outperforms conventional algorithms in terms of accuracy, robustness, and computational efficiency. This research provides a reliable and effective tool for proactive hazard management in coal mines, contributing to enhanced operational safety and risk mitigation.