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Early Warning of the Construction Safety Risk of a Subway Station Based on the LSSVM Optimized by QPSO

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成果类型:
期刊论文
作者:
Zhang, Leian;Wang, Junwu;Wu, Han;Wu, Mengwei;Guo, Jingyi;...
通讯作者:
Junwu Wang
作者机构:
[Zhang, Leian; Wang, Junwu] Wuhan Univ Technol, Sch Civil Engn & Architecture, Wuhan 430062, Peoples R China.
[Wu, Han] Nanchang Univ, Sch Civil Engn & Architecture, Nanchang 330047, Jiangxi, Peoples R China.
[Wu, Mengwei] Wuhan Polytech Univ, Sch Civil Engn & Architecture, Wuhan 430024, Peoples R China.
[Guo, Jingyi] Hubei Univ Arts & Sci, Sch Civil Engn & Architecture, Xiangyang 441021, Peoples R China.
[Wang, Shengmin] Wuhan Univ Technol, Sch Safety Sci & Emergency Management, Wuhan 430062, Peoples R China.
通讯机构:
[Junwu Wang] S
School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430062, China<&wdkj&>Author to whom correspondence should be addressed.
语种:
英文
关键词:
early warning;construction safety risk;subway station;LSSVM;QPSO;accident causation theory
期刊:
Applied Sciences-Basel
ISSN:
2076-3417
年:
2022
卷:
12
期:
11
页码:
5712-
基金类别:
Conceptualization, L.Z., S.W. and H.W.; methodology, L.Z.; software, H.W. and M.W.; validation, J.W., L.Z. and H.W.; formal analysis, L.Z. and J.G.; investigation, H.W.; data curation, L.Z. and H.W.; writing—original draft preparation, J.W., L.Z., M.W., and H.W.; writing—review and editing, J.W., S.W. and M.W.; supervision, J.W.; project administration, J.W.; funding acquisition, J.W. All authors have read and agreed to the published version of the manuscript. This research was funded by the Science and Technology Project of Wuhan Urban and Rural Construction Bureau, China (201943), and the 2018 Special Research Project of China Construction Third Engineering Bureau (20181208).
机构署名:
本校为其他机构
院系归属:
土木工程与建筑学院
摘要:
Subway station projects are characterized by complex construction technology, complex site conditions, and being easily influenced by the surrounding environment; thus, construction safety accidents occur frequently. In order to improve the computing performance of the early risk warning system in subway station construction, a novel model based on least-squares support vector machines (LSSVM) optimized by quantum-behaved particle swarm optimization (QPSO) was proposed. First, early warning factors from five aspects (man, machine, management, m...

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