[Neural network analysis of mechanization's impact on coal miner's occupational health].

H M Yu, Y P Du
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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.

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[机械化对煤矿工人职业健康影响的神经网络分析]。
为厘清机械化对矿工职业健康影响的传导机制,为煤炭行业发展兼顾健康与效率的新型优质生产力提供实证依据。2022 年 8 月,我们选取典型煤矿,基于全连接神经网络模型,通过问卷调查构建了矿工职业健康综合评价指标。采用贝叶斯模型验证了机械化水平对矿工职业健康的影响。我们发现:职业病预测概率可作为衡量职业健康水平的综合指标,为职业病的早期干预和预防提供依据。机械化可直接促进矿工职业健康水平的提高,也可通过影响危害程度和工作强度间接影响职业健康水平。机械化对工作强度的间接影响为正,机械化对危害水平的间接影响为正。呈现 "倒 U 型 "过程的机械化突破半机械化水平将实现卫生防护的规模经济,其对职业危害防治的影响将由负转正。
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来源期刊
中华劳动卫生职业病杂志
中华劳动卫生职业病杂志 Medicine-Medicine (all)
CiteScore
1.00
自引率
0.00%
发文量
9764
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