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

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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Bibliographic Details
Main Authors: Cheng Chen, Guan-Nian Chen, Song Feng, Xiao-Zhen Fan, Liang-Tong Zhan, Yun-Min Chen
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2025-08-01
Series:Underground Space
Subjects:
Automated monitoring
Extreme learning machine
Lateral displacement
Deep excavation
Particle swarm optimization
Predictive modeling
Online Access:http://www.sciencedirect.com/science/article/pii/S2467967425000406
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