Using data mining and complex network analysis for causal analysis of impact factors in hazardous chemical accidents.

In this paper, an innovative two-layer network model was established to analyze safety risk factors for hazardous chemical accidents(SRFHCA). Firstly, potential safety risk factors were identified through the dataset from human, equipment, management, and environmental dimensions. Then, association rules learning was introduced to learn the associations between different factors. Finally, a two-layer complex network model was constructed to identify the critical factors. Our proposed methods and the corresponding results provide decision support to reduce the risk of hazardous chemical accidents. [ABSTRACT FROM AUTHOR]