| contributor author | Al-Ammari, Wahib A. | |
| contributor author | Sleiti, Ahmad K. | |
| contributor author | AbuShanab, Yazeed | |
| contributor author | Hamilton, M. | |
| contributor author | Rashid Hasan, Abu | |
| contributor author | Hassan, Ibrahim | |
| contributor author | Kaan, M. S. | |
| contributor author | Rezaei-Gomari, S. | |
| contributor author | Rahman, Mohammad Azizur | |
| date accessioned | 2026-08-20T12:04:28Z | |
| date available | 2026-08-20T12:04:28Z | |
| date copyright | 2025/09/27 | |
| date issued | 2026 | |
| identifier other | JPSEA2.PSENG-1813.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4313061 | |
| description abstract | AbstractLeak detection and localization in offshore gas pipelines is critical in preventing
hazardous events and minimizing operational and economic losses. This study presents
a structured machine learning (ML) framework capable of detecting and ... | |
| publisher | American Society of Civil Engineers | |
| title | Development of Machine Learning Models for Multiple Leak Detection in Offshore Gas Pipelines under Single- and Multiphase Flow Conditions | |
| type | Journal Article | |
| journal volume | 17 | |
| journal issue | 1 | |
| journal title | Journal of Pipeline Systems Engineering and Practice | |
| identifier doi | 10.1061/JPSEA2.PSENG-1813 | |
| journal fristpage | 04025092-1 | |
| journal lastpage | 04025092-20 | |
| page | 20 | |
| tree | Journal of Pipeline Systems Engineering and Practice:;2026:;Volume ( 017 ):;issue: 001 | |
| contenttype | Fulltext | |
