Root Cause Correlation Analysis of Chemical Enterprise Accident

doi:10.3969/j.issn.1006-2475.2020.10.001

Abstract

Abstract: The root causes of chemical accidents are mainly caused by the unsafe behavior of people, the unsafe state of machinery or materials, etc. Their essence is the defect of enterprise management. Mining the relationships between root causes, root causes and accidents is the key to prevent accidents and improve the level of enterprise safety management. Since the existing root cause analysis of accident investigation and the safety management index system are sparsely correlated, it is difficult to mine the correlations between management defects and accident evolution. So, collaborative filtering algorithm is used to fill in the missing score data in the accident investigation. The association rule algorithm based on the weighted support degree is used to mine the strong association rules between the root causes of the accidents, the root cause and the accident attribute. The experimental results show that compared with the existing algorithms, the association analysis algorithm based on weighted support can recommend more high-risk enterprises potential safety hazards and the evolutionary correlations between safety hazards and accidents, so as to scientifically guide the safe production of enterprises, realize the risk warning and accident prevention for the production process.

Key words: enterprise safety production, root cause correlation analysis, collaborative filtering, accident evolution, weighted support

CLC Number:

TP391

CHEN Zhuo, LI Xin, DU Jun-wei, YUAN Xi-ming. Root Cause Correlation Analysis of Chemical Enterprise Accident[J]. Computer and Modernization, 2020, 0(10): 1-6.

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