Developing a predictive model using multivariate analysis and Long Short-Term Memory (LSTM) to assess corrosion degradation in mining pipeline thickness.

Developing a predictive model using multivariate analysis and Long Short-Term Memory (LSTM) to assess corrosion degradation in mining pipeline thickness.

Pipeline corrosion has significant impacts on the human, economic, and natural environment. To help better detect and prevent it over time, in this paper, we propose a multivariate approach using machine learning. More precisely, we propose to study the evolution of the thickness of the mining pipel...

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Bibliographic Details
Main Authors:	Kalidou Moussa Sow, Nadia Ghazzali
Format:	Article
Language:	English
Published:	LibraryPress@UF 2024-05-01
Series:	Proceedings of the International Florida Artificial Intelligence Research Society Conference
Online Access:	https://journals.flvc.org/FLAIRS/article/view/135320
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