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Based on a comprehensive analysis of different work and management indicators, as well as the quantitative assessment outcomes of the implemented personal safety responsibility system, this study proposes the utilization of computer intelligent warning technology within the power supply enterprise responsibility system. This technology enables the automatic analysis of the entire operational process of the power supply enterprise responsibility system, facilitating the examination of the responsibility system at various hierarchical levels within the organization. This paper aims to propose the establishment of evaluation indicators derived from the components of power supply enterprise safety responsibility system construction, and subsequently develop a multi-level responsibility evaluation index system. The dynamic evaluation method is employed for the computation of the evaluation value and the establishment of the pre-control algorithm. The evaluation data of the full staff safety responsibility system is monitored in real-time, and any abnormal detection is promptly addressed. Upon the detection of abnormalities, the determination of warning execution conditions and warning levels is conducted by considering the warning indicators associated with the abnormal data. Based on this criterion, a determination is made regarding the issuance of a warning. When a warning is issued, it triggers the generation of corresponding warning information based on the warning level. This real-time warning information is then stored in the database.
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Zhang et al. (2024) studied this question.
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