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This is a Quantitative Study study (also classified as: Experimental Study).

September 20, 2025BuildingsOpen Access

Hierarchical Prediction of Subway-Induced Ground Settlement Based on Waveform Characteristics and Machine Learning with Applications to Building Safety

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This framework predicts ground settlement in building environments during subway construction, indicating risk management strategies.

The hierarchical prediction model enhances building safety by accurately forecasting ground settlement patterns.
Monitoring data from Urumqi Metro reveals that machine learning methods like AM-LSTM outperform traditional models.
Analyses identified settlement curve types using Fréchet distance, allowing tailored predictive modeling for each type.
Model validation on Urumqi Metro Line 2 illustrates its effectiveness in improving safety management in construction zones.

Meng et al. (2025) studied this question.

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