| contributor author | Chermime, Nasser | |
| contributor author | Bouamrane, Ali | |
| contributor author | Derdous, Oussama | |
| contributor author | Dahri, Noura | |
| contributor author | Bouziane, Mohamed T | |
| contributor author | Abida, Habib | |
| contributor author | Bao Pham, Quoc | |
| date accessioned | 2026-08-20T12:06:22Z | |
| date available | 2026-08-20T12:06:22Z | |
| date copyright | 2026/02/26 | |
| date issued | 2026 | |
| identifier other | JPSEA2.PSENG-1946.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4313104 | |
| description abstract | AbstractIn recent years, researchers and policymakers have focused on leaks in water systems
as a critical issue because of their negative impact on human society. Most classical
methods can only provide approximate leakage locations, typically ... | |
| publisher | American Society of Civil Engineers | |
| title | Identifying Leaks in Water Distribution Networks Using Deep Learning Neural Network and Frequency Ratio Models | |
| type | Journal Article | |
| journal volume | 17 | |
| journal issue | 2 | |
| journal title | Journal of Pipeline Systems Engineering and Practice | |
| identifier doi | 10.1061/JPSEA2.PSENG-1946 | |
| journal fristpage | 04026017-1 | |
| journal lastpage | 04026017-9 | |
| page | 9 | |
| tree | Journal of Pipeline Systems Engineering and Practice:;2026:;Volume ( 017 ):;issue: 002 | |
| contenttype | Fulltext | |
