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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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
LibraryPress@UF
2024-05-01
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| 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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