| contributor author | Shangguan, Lingxiao | |
| contributor author | Lu, Guoyang | |
| contributor author | Wu, Zhe | |
| contributor author | Xu, Zijun | |
| contributor author | Li, Hanxi | |
| date accessioned | 2026-08-20T21:25:36Z | |
| date available | 2026-08-20T21:25:36Z | |
| date copyright | 2025/08/20 | |
| date issued | 2025 | |
| identifier other | JCCEE5.CPENG-6782.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4314433 | |
| description abstract | AbstractAccurate pavement roughness assessment is critical for effective pavement management.
Connected car data provides a cost-effective way to predict the pavement roughness
based on the acceleration data. This paper proposes a novel prediction model ... | |
| publisher | American Society of Civil Engineers | |
| title | Connected Car-Based Pavement Roughness Prediction Using CNN Model and Signal Decomposition Technique | |
| type | Journal Article | |
| journal volume | 39 | |
| journal issue | 6 | |
| journal title | Journal of Computing in Civil Engineering | |
| identifier doi | 10.1061/JCCEE5.CPENG-6782 | |
| journal fristpage | 04025099-1 | |
| journal lastpage | 04025099-13 | |
| page | 13 | |
| tree | Journal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 006 | |
| contenttype | Fulltext | |
