Evaluating regulatory influences on coal mine accidents in China using a fuzzy multi-criteria decision-making approach.

Abstract

Amidst the global surge in industrialization, frequent coal mine safety incidents pose significant risks to miners' lives and environmental stability. This study employs Fuzzy Multi-Criteria Decision-Making (FMCDM) to quantitatively analyze regulatory factors affecting coal mine safety in China from 2012 to 2022, identifying key elements that influence accident risks and regional policy disparities. By integrating Structural Equation Modeling (SEM), Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL), and Gaussian Fuzzy Monte Carlo Analytic Network Process (GFMANP), a comprehensive risk assessment model is developed. This multifaceted approach addresses the limitations of traditional assessment methods, not only identifying the key regulatory factors impacting coal mine safety but also quantifying their influence and interrelationships. The findings reveal a strong correlation between design schemes and management systems (correlation coefficient 0.4931), emphasizing their interdependence and the importance of an integrated approach to safety management. In addition, the results show that technical documents and Southwest factors have the highest risk values (0.1506 and 0.2050, respectively), which provide a detailed risk assessment for different regions of China and are crucial for developing security strategies for different regions. Based on these findings, the recommendations include optimizing the synergy between design schemes and management systems, enhancing technical document management, and developing region-specific safety strategies to reduce the risks of coal mine accidents and improve safety management standards.