Abstract
In this paper, we focus on oil & gas storage and transportations facilities (OSTF), and research on the risk assessment and the hysteretic nature of contingency plans. First, with principal component analysis to select forewarning indicators, we structure a risk assessment model based on logistic regression, and the model has strong robustness. What’s more, we link multidimensional data with different contingency plans by K-means Cluster Analysis. In conclusion, we realize the accuracy of assessment of OSTF from the view of data mining, and come up with a new management mode including “Big data monitoring---Intelligent assessment---Automatically forewarning---The advance of emergency measures” with the help of MIS to realize the timeliness of contingency management.
Published Version
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