| contributor author | Shen, Yonggang | |
| contributor author | Lin, Qipeng | |
| contributor author | Wang, Haoli | |
| contributor author | Yu, Zhenwei | |
| date accessioned | 2026-08-20T21:05:33Z | |
| date available | 2026-08-20T21:05:33Z | |
| date copyright | 2025/06/03 | |
| date issued | 2025 | |
| identifier other | JWRMD5.WRENG-6899.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4313936 | |
| 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 ... | |
| publisher | American Society of Civil Engineers | |
| title | Acoustic Leak Detection in Water Supply Pipelines Based on an Adaptive Multitask Model | |
| type | Journal Article | |
| journal volume | 151 | |
| journal issue | 8 | |
| journal title | Journal of Water Resources Planning and Management | |
| identifier doi | 10.1061/JWRMD5.WRENG-6899 | |
| journal fristpage | 04025031-1 | |
| journal lastpage | 04025031-13 | |
| page | 13 | |
| tree | Journal of Water Resources Planning and Management:;2025:;Volume ( 151 ):;issue: 008 | |
| contenttype | Fulltext | |