石油与天然气化工2026，Vol.55Issue(2)：159-165,7.DOI:10.3969/j.issn.1007-3426.2026.02.019
基于GA-PSO-XGBoost模型的城市燃气管道风险评价方法
Risk assessment method of urban gas pipeline based on GA-PSO-XGBoost model
彭善碧 1王鸿扬 1郑鹤2
作者信息
- 1. 西南石油大学土木工程与测绘学院
- 2. 中国石油西南油气田公司天然气研究院
- 折叠
摘要
Abstract
Objective Aiming at the limitations of the traditional risk assessment methods in the risk assessment of urban gas pipelines,such as the difficulty of quantitative analysis and strong subjectivity,a gas pipeline risk assessment model based on machine learning is proposed.Method Based on the genetic algorithm(GA),particle swarm optimization(PSO),and eXtreme gradient boosting(XGBoost)algorithm,the GA-PSO-XGBoost urban gas pipeline risk assessment model is constructed.The model uses the GA-PSO hybrid algorithm to optimize the hyperparameters of XGBoost,thereby improving the accuracy of urban gas pipeline risk assessment.Result The model test results show that the mean square error(MSE),mean absolute error(MAE)and coefficient of determination(R2)of the GA-PSO-XGBoost model are 4.126 4,1.493 9 and 99.114 6%,respectively,which verifies the high accuracy and reliability of the model.Conclusion The GA-PSO-XGBoost model provides a new method for the risk assessment of urban gas pipeline,which has an important application value for improving the safety management of gas pipeline.关键词
风险评价/城市燃气管道/遗传算法/粒子群优化/极限梯度提升Key words
risk assessment/urban gas pipeline/GA/PSO/XGBoost引用本文复制引用
彭善碧,王鸿扬,郑鹤..基于GA-PSO-XGBoost模型的城市燃气管道风险评价方法[J].石油与天然气化工,2026,55(2):159-165,7.
