Average Corrosion Rate Prediction Model for Buried Oil and Gas Pipelines Based on SSA-LightGBM

Average Corrosion Rate Prediction Model for Buried Oil and Gas Pipelines Based on SSA-LightGBM

Corrosion represents a major cause of damage and leakage in oil and gas pipelines, making accurate corrosion rate prediction critical for operational safety. This study establishes an average corrosion rate prediction model using the Sparrow Search Algorithm-optimized Light Gradient Boosting Machine...

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Bibliographic Details
Main Authors: Weigang Fu, Haitao Wang, Kuankuan Zhang, Xia Wang, Kunlun Chen, Chunmei Sun, Zhengwei Wang, Liuyang Song, Niannian Wang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Average corrosion rate
LightGBM
machine learning optimization
oil and gas pipeline
sparrow search algorithm
SPDA
Online Access:https://ieeexplore.ieee.org/document/11029024/
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https://ieeexplore.ieee.org/document/11029024/

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