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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Detaylı Bibliyografya
Asıl Yazarlar:	Cheng Chen, Guan-Nian Chen, Song Feng, Xiao-Zhen Fan, Liang-Tong Zhan, Yun-Min Chen
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	KeAi Communications Co., Ltd. 2025-08-01
Seri Bilgileri:	Underground Space
Konular:	Automated monitoring Extreme learning machine Lateral displacement Deep excavation Particle swarm optimization Predictive modeling
Online Erişim:	http://www.sciencedirect.com/science/article/pii/S2467967425000406
Etiketler:	Etiketle Etiket eklenmemiş, İlk siz ekleyin!

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

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