Machine Learning and Data Science in Geotechnics

Fuente: DOAJ
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Bibliographische Detailangaben
Format: Revista científica
Sprache:EN
Veröffentlicht: Emerald Publishing 2026
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format Revista científica
id doaj_https___doaj_org_toc_3029-0422
institution DOAJ
language EN
publishDate 2026
publisher Emerald Publishing
record_format doaj
spellingShingle Machine Learning and Data Science in Geotechnics
machine learning in geotechnics
artificial intelligence for infrastructure resilience
big data and statistical analysis in soil mechanics
sustainable geotechnical engineering
geostructure modeling and optimization
micro-to-macro scale geotechnical applications
Engineering (General). Civil engineering (General)
TA1-2040
title Machine Learning and Data Science in Geotechnics
topic machine learning in geotechnics
artificial intelligence for infrastructure resilience
big data and statistical analysis in soil mechanics
sustainable geotechnical engineering
geostructure modeling and optimization
micro-to-macro scale geotechnical applications
Engineering (General). Civil engineering (General)
TA1-2040
url https://doaj.org/toc/3029-0422