Interpretable CEEMDAN-SMA-LSSVM hybrid model for predicting shield tunnel-induced settlement

Accurate and interpretable prediction of shield tunnel-induced settlement poses a significant challenge due to the complex interplay of various influencing factors. This paper proposes a novel interpretable hybrid model that combines complete ensemble empirical mode decomposition with adaptive noise...

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Veröffentlicht in:	Journal of Rock Mechanics and Geotechnical Engineering Jg. 17; H. 10; S. 6179 - 6194
Hauptverfasser:	Meng, Shaoqiang, Shi, Zhenming, Gutierrez, Marte
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.10.2025
Schlagworte:	Geotechnical engineering Machine learning Shapley additive explanations (SHAP) Swarm intelligence optimization algorithm Geotechnical engineering Swarm intelligence optimization algorithm Shapley additive explanations (SHAP) Machine learning
ISSN:	1674-7755
Online-Zugang:	Volltext
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