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AI-Based Safety Production Accident Prevention Mechanism in Smart Enterprises
Abstract
Enterprises have accumulated a large number of accident data resources for safety production, but the corresponding safety production information processing capacity is insufficient, resulting in the value of massive data not being effectively used, and further restricting the in-depth study of accidents. Enterprise safety managers cannot learn lessons from historical accidents in a timely manner and effectively prevent them, leading to repeated occurrences of similar accidents. Therefore, based on the above problems, this paper aims to construct a mining process for the cause of safety production accidents based on LDA topic model. According to the accident data structure, select a data mining method suitable for its structural characteristics to maximize the utilization of accident data. According to the sequence of initial identification of accident information, discovery of safety problems, and transformation of safety knowledge, the valuable information in historical accident data can be fully excavated, so as to provide effective suggestions for accident prevention.
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