Leveraging Machine Learning for Pipeline Condition Assessment

IF 1.8 4区工程技术 Q3 ENGINEERING, CIVIL

Journal of Pipeline Systems Engineering and Practice Pub Date : 2023-08-01 DOI:10.1061/jpsea2.pseng-1464

Hongfang Lu, Zhao Xu, Xulei Zang, D. Xi, T. Iseley, John C. Matthews, Niannian Wang

引用次数: 1

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利用机器学习进行管道状况评估

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Pipeline Systems Engineering and Practice ENGINEERING, CIVIL-WATER RESOURCES

CiteScore

3.80

自引率

10.00%

发文量

期刊介绍： The Journal of Pipeline Systems Engineering and Practice is a professional, authoritative technical resource that reports on a broad range of topics pertaining to the planning, engineering, design, construction, renewal, safety, operation and maintenance, asset management, environmental aspects, and sustainability of pipeline systems. An important technical reference for researchers and practitioners from academia, industry, and government, it presents in-depth information on water distribution and transmission systems, wastewater collection systems (gravity and force mains), storm sewers and drainage structures/culverts, oil, gas, industrial, slurry, pneumatic and capsule pipelines, as well as conduit applications for power and communication cables.