Predicting excavation-induced lateral displacement using improved particle swarm optimization and extreme learning machine with sparse measurements

Monitoring lateral displacement in deep excavation projects is crucial for structural stability and safety. Traditional methods, like manual inclinometers, are accurate but costly and labor-intensive. Automated systems provide real-time data but face challenges with dense sensor placement and high c...

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Detalhes bibliográficos

Principais autores:	Cheng Chen, Guan-Nian Chen, Song Feng, Xiao-Zhen Fan, Liang-Tong Zhan, Yun-Min Chen
Formato:	Artigo
Idioma:	Inglês
Publicado em:	KeAi Communications Co., Ltd. 2025-08-01
coleção:	Underground Space
Assuntos:	Automated monitoring Extreme learning machine Lateral displacement Deep excavation Particle swarm optimization Predictive modeling
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S2467967425000406
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