| contributor author | Xiao, Feng | |
| contributor author | Song, Qianhong | |
| contributor author | Gao, Jie | |
| contributor author | Yang, Shunxin | |
| contributor author | Chen, Huapeng | |
| date accessioned | 2026-08-20T12:02:43Z | |
| date available | 2026-08-20T12:02:43Z | |
| date copyright | 2026/01/29 | |
| date issued | 2026 | |
| identifier other | JPEODX.PVENG-1967.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4313019 | |
| description abstract | AbstractPavement maintenance and rehabilitation (M&R) data anomalies critically undermine
pavement management system (PMS) reliability, yet conventional artificial neural network
(ANN)-based correction methods fail to capture inherent temporal ... | |
| publisher | American Society of Civil Engineers | |
| title | Anomaly Detection and Correction Framework for Pavement Maintenance and Rehabilitation Data Based on LSTM | |
| type | Journal Article | |
| journal volume | 152 | |
| journal issue | 2 | |
| journal title | Journal of Transportation Engineering, Part B: Pavements | |
| identifier doi | 10.1061/JPEODX.PVENG-1967 | |
| journal fristpage | 04026007-1 | |
| journal lastpage | 04026007-13 | |
| page | 13 | |
| tree | Journal of Transportation Engineering, Part B: Pavements:;2026:;Volume ( 152 ):;issue: 002 | |
| contenttype | Fulltext | |
