Corrosion Rate Prediction of Buried Oil and Gas Pipelines: A New Deep Learning Method Based on RF and IBWO-Optimized BiLSTM–GRU Combined Model
The corrosion of oil and gas pipelines represents a significant factor influencing the safety of these pipelines. The extant research on intelligent algorithms for assessing corrosion rates in pipelines has primarily focused on static evaluation methods, which are inadequate for providing a comprehe...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/17/23/5824 |
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