Analysis of Gas Pipeline Failure Factors Based on the Novel Bayesian Network by Machine Learning Optimization

Analysis of Gas Pipeline Failure Factors Based on the Novel Bayesian Network by Machine Learning Optimization

Assessing the failure of urban gas pipelines is crucial for identifying risk factors and preventing gas accidents that result in economic losses and casualties. Most previous studies on gas pipeline failure assessment are based on the basic Bayesian network (BN). However, the conditional probability...

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Bibliographic Details
Main Authors: Shuangqing Chen, Shun Zhou, Zhe Xu, Yongbin Liu, Bing Guan, Xiaoyu Jiang, Wencheng Li
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Bayesian network
gas pipeline
machine learning
noisy-OR gate model
risk assessment
Online Access:https://ieeexplore.ieee.org/document/10869343/
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