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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Bibliographic Details
Main Authors: Jiong Wang, Zhi Kong, Jinrong Shan, Chuanjia Du, Chengjun Wang
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Energies
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Online Access:https://www.mdpi.com/1996-1073/17/23/5824
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