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Intelligent Classification of Rocks in Mountain Highway Tunnels Using ISSA-ELM Model

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成果类型:
期刊论文
作者:
Shurong Feng;Yongjia Hu;Da Hu*;Yongsuo Li;Ze Tan;...
通讯作者:
Da Hu
作者机构:
[Shurong Feng] Hunan Provincial Key Laboratory of Key Technology on Hydropower Development, PowerChina Zhongnan Engineering Corporation Limited, Changsha, China
[Yongjia Hu; Rong Hu] School of Civil Engineering, Hunan City University, Yiyang, China
Hunan Engineering Research Centre for Structural Safety and Disaster Prevention of Urban Underground Infrastructure, Hunan City University, Yiyang, China
[Da Hu; Yongsuo Li; Ze Tan] Hunan Engineering Research Centre for Structural Safety and Disaster Prevention of Urban Underground Infrastructure, Hunan City University, Yiyang, China<&wdkj&>School of Civil Engineering, Hunan City University, Yiyang, China
通讯机构:
[Da Hu] H
Hunan Engineering Research Centre for Structural Safety and Disaster Prevention of Urban Underground Infrastructure, Hunan City University, Yiyang, China<&wdkj&>School of Civil Engineering, Hunan City University, Yiyang, China
语种:
英文
关键词:
Intelligent classification of surrounding rock;Stability of surrounding rock;Deep learning;Extreme learning machine;ISSA-ELM combined model
期刊:
Geotechnical and Geological Engineering
ISSN:
0960-3182
年:
2024
卷:
42
期:
8
页码:
7385-7405
基金类别:
The authors have not disclosed any funding.
机构署名:
本校为通讯机构
院系归属:
土木工程学院
摘要:
During construction, mountainous highway tunnels are often subjected to complex forces and are prone to large deformations, which severely affect the long-term stability of the surrounding rock. Therefore, it is crucial to explore rapid identification and intelligent classification methods for rock surrounding tunnels. In response to the above issues, this study proposes a new intelligent classification and prediction method for rock surrounding highway tunnels on the basis of an index classification system of the environmental characteristics ...

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