| dc.contributor.author | Shen, Yonggang | |
| dc.contributor.author | Lin, Qipeng | |
| dc.contributor.author | Wang, Haoli | |
| dc.contributor.author | Yu, Zhenwei | |
| dc.date.accessioned | 2026-08-20T21:05:33Z | |
| dc.date.available | 2026-08-20T21:05:33Z | |
| dc.date.copyright | 2025/06/03 | |
| dc.date.issued | 2025 | |
| dc.identifier.other | JWRMD5.WRENG-6899.pdf | |
| dc.identifier.uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4313936 | |
| dc.description.abstract | AbstractWith the outstanding performance of convolutional neural networks in tasks such as
image classification, data-driven deep learning models have been widely applied in
the field of pipeline leak detection. Acoustic leak detection primarily consists ... | |
| dc.publisher | American Society of Civil Engineers | |
| dc.title | Acoustic Leak Detection in Water Supply Pipelines Based on an Adaptive Multitask Model | |
| dc.type | Journal Article | |
| dc.journal.volume | 151 | |
| dc.journal.issue | 8 | |
| dc.journal.title | Journal of Water Resources Planning and Management | |
| dc.identifier.doi | 10.1061/JWRMD5.WRENG-6899 | |
| dc.journal.fristpage | 04025031-1 | |
| dc.journal.lastpage | 04025031-13 | |
| dc.page | 13 | |
| dc.tree | Journal of Water Resources Planning and Management:;2025:;Volume ( 151 ):;issue: 008 | |
| dc.contenttype | Fulltext | |
