Generation of Synthetic Data for the Analysis of the Physical Stability of Tailing Dams through Artificial Intelligence

Generation of Synthetic Data for the Analysis of the Physical Stability of Tailing Dams through Artificial Intelligence

In this research, we address the problem of evaluating physical stability (PS) to close tailings dams (TD) from medium-sized Chilean mining using artificial intelligence (AI) algorithms. The PS can be analyzed through the study of critical variables of the TD that allow estimating different potentia...

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Bibliographic Details
Main Authors: Fernando Pacheco, Gabriel Hermosilla, Osvaldo Piña, Gabriel Villavicencio, Héctor Allende-Cid, Juan Palma, Pamela Valenzuela, José García, Alex Carpanetti, Vinicius Minatogawa, Gonzalo Suazo, Andrés León, Ricardo López, Gullibert Novoa
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Mathematics
Subjects:
tailings dams
physical stability
machine learning
data augmentation
generative adversarial networks
artificial neural networks
Online Access:https://www.mdpi.com/2227-7390/10/23/4396

Internet

https://www.mdpi.com/2227-7390/10/23/4396

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