Study on early warning of safety risk in underground cavern group construction under neural network paradigm

doi:10.16265/j.cnki.issn1003-3033.2018.02.031

Abstract

Abstract: In order to protect the safety of underground cavern group construction workers and prevent accidents, the BP neural network method was used to study early warning of safety risks in the construction of underground caverns. Firstly, through the analysis of the influencing factors of construction safety of underground caverns, a warning index system was constructed. After collecting 1 000 sets of training samples, the network parameters were set and debugged. After the success of the network training, a safety risk early warning analysis for the underground cavern group during construction was carried out. Then the underground caverns under construction in a certain place were taken as an example to verify the effectiveness of the early warning method. The results show that the early warning method can be used to quickly know the current safety status of and the trend in variation of risk in the underground caverns construction, and is helpful in taking effective measures in advance for improving the safety management level of underground caverns construction.

Key words: underground cavern group, construction safety, risk, early warning indicator, BP neural network

CLC Number:

X948

JIANG Xin, DU Haiwen, YUAN Xuan, HU Wenjia, ZHENG Xiazhong, SUN Zhengxi. Study on early warning of safety risk in underground cavern group construction under neural network paradigm[J]. China Safety Science Journal, 2018, 28(2): 181-186.

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