Machine-learning-based ground sink susceptibility evaluation using underground pipeline data in Korean urban area

Ground subsidence caused by natural factors, including groundwater, has been extensively researched. However, there have been few studies on ground sink caused mainly by artifacts, including underground pipelines in urban areas. This paper proposes a method of predicting ground sink susceptibility c...

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Detalles Bibliográficos
Autores principales: Park, Jun Hwan, Kang, Junggoo, Kang, Jaemo, Mun, Duhwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9719511/
https://www.ncbi.nlm.nih.gov/pubmed/36463331
http://dx.doi.org/10.1038/s41598-022-25237-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9719511/
https://www.ncbi.nlm.nih.gov/pubmed/36463331
http://dx.doi.org/10.1038/s41598-022-25237-8

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