Neural network analysis of mechanization's impact on coal miner's occupational health
10.3760/cma.j.cn121094-20231109-00103
- VernacularTitle:机械化对矿工职业健康影响的神经网络分析
- Author:
Haimiao YU
1
;
Yipei DU
Author Information
1. 中国矿业大学经济管理学院，徐州 221116
- Keywords:
Coal mine;
Occupational health;
Mechanization;
Fully connected neural network;
Bayesian network
- From:
Chinese Journal of Industrial Hygiene and Occupational Diseases
2024;42(5):374-380
- CountryChina
- Language:Chinese
-
Abstract:
In order to clarify the transmission mechanism of the impact of mechanization on the occupational health of miners and to provide empirical evidence for the development of new quality productivity in the coal industry that balances health and efficiency. In August 2022, we selected a typical coal mine, constructed a comprehensive evaluation index of miners' occupational health through a questionnaire survey based on the fully connected neural network model. A Bayesian model was used to verify the influence of mechanization level on miners' occupational health. We found that: the predicted probability of occupational diseases could be used as a comprehensive indicator of the level of occupational health, providing a basis for early intervention and prevention of occupational diseases. Mechanization could directly promote the improvement of miners' occupational health level, and also indirectly affect occupational health level by influencing hazards level and work intensity. The indirect effect of mechanization on work intensity was positive, and the indirect effect of mechanization on hazards level was positive. Presented the "inverted U-shaped" process in the mechanization breakthrough semi-mechanized level would realize the economies of scale of health protection, its impact on the prevention and control of occupational hazards would turn from negative to positive.
