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Explainable machine learning-based land subsidence susceptibility mapping: from feature importance to individual model contributions in ensembled system

Crossref DOI link: https://doi.org/10.1007/s12145-025-01915-9

Published Online: 2025-05-20

Published Print: 2025-06

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Yu, Bofan

Xing, Huaixue

Ge, Weiya

Yan, Jiaxing

Li, Yun-an
Funding

Funding for this research was provided by:

Laboratory of Geological Safety of Underground Space in Coastal Cities, Ministry of Natural Resources (Project No. BHKF2022Z02)
License Information

Text and Data Mining valid from 2025-05-20

Version of Record valid from 2025-05-20
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Article History

Received: 24 November 2024

Accepted: 8 May 2025

First Online: 20 May 2025

Declarations

:

: This study does not involve any human participants or animals. Therefore, ethical approval and consent to participate are not applicable.

: The authors declare no competing interests.

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