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In this paper, we analyze the current situation of gas filling station, find out the risk factors affecting the safety of gas stations, and propose a new algorithm based on BP neural network model. With the historical monitoring data of gas filling stations, BP neural network model can be used to approximate any nonlinear continuous function, and the historical data of each index are studied. The data were randomly divided into training data and test data. Reasonable selection of network layer number and node number, a l arge number of experiments were carried out, and the hidden rule is established. The risk prediction model based on BP neural network system was established. The accuracy of the model was verified by Matlab simulation. This study is conducive to improve the safety performance of the filling station, and find out the potential danger in advance, improve the efficiency of accident rescue, and play an important role in reducing the accident loss.

The application of BP neural network in the safety warning of gas stations