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Interpretable Ensemble Machine Learning for Liquefaction Risk Prediction

This paper presents a comprehensive machine learning (ML) framework for predicting liquefaction risk, a crucial aspect of seismic hazard assessment. A benchmark geotechnical dataset with multi-dimensional input features was used to evaluate several ML classifiers, followed by hyperparameter optimiza...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Doszhan Tuzelbayev, Sung-Woo Moon, Minho Lee, Shynggys Abdialim, Elijah Adebayonle Aremu, Alfrendo Satyanaga, Jong Kim
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2025-11-01
Schriftenreihe:Infrastructures
Schlagworte:
liquefaction
machine learning
ensemble learning
hyperparameter optimization
SHAP analysis
Online-Zugang:https://www.mdpi.com/2412-3811/10/11/304
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