Using Machine Learning for Predicting Collapse extending in Abandoned Underground Mines

Authors

Institutions

Publication Details

Journal
SPIRE - Sciences Po Institutional REpository
Published
2025-06-16
Primary Topic
Tailings Management and Properties
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Using Machine Learning for Predicting Collapse extending in Abandoned Underground Mines

Lina‐María Guayacán‐Carrillo, Nathalie Conil, A. Kadri
SPIRE - Sciences Po Institutional REpository
Tailings Management and Properties
article

Using Machine Learning for Predicting Collapse extending in Abandoned Underground Mines

Lina‐María Guayacán‐Carrillo, Nathalie Conil, A. Kadri
article en

Abstract

No abstract available for this paper.
SPIRE - Sciences Po Institutional REpository
École nationale des ponts et chaussées (FR), Laboratoire Navier (FR), Institut national de l'environnement industriel et des risques (FR)
Openalex Percentile: Top 64%
Tailings Management and Properties
Open Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Using Machine Learning for Predicting Collapse extending in Abandoned Underground Mines — Lina‐María Guayacán‐Carrillo, Nathalie Conil, et al. · SPIRE - Sciences Po Institutional REpository (2025) | TGRS Research Map | TGRS