| dc.contributor.author | Shen, Boyan | |
| dc.contributor.author | Wang, Zhiwen | |
| dc.contributor.author | Ling, Guobi | |
| dc.contributor.author | Wang, Haoxu | |
| dc.contributor.author | Cheng, Xiaolong | |
| dc.contributor.author | Miao, Wei | |
| dc.date.accessioned | 2026-08-20T20:55:58Z | |
| dc.date.available | 2026-08-20T20:55:58Z | |
| dc.date.copyright | 2025/11/03 | |
| dc.date.issued | 2026 | |
| dc.identifier.other | JTEPBS.TEENG-9240.pdf | |
| dc.identifier.uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4313691 | |
| dc.description.abstract | AbstractIn intelligent transport systems (ITS), accurate and real-time traffic flow prediction
is essential to reduce congestion and manage transport. Numerous existing studies
have used hybrid models to extract various intrinsic patterns of traffic flow ...Practical ApplicationsIn intelligent transportation management, accurately predicting road traffic flow
is crucial for alleviating congestion and optimizing road networks. Traditional methods
are easily disrupted by noise in the data and struggle to fully ... | |
| dc.publisher | American Society of Civil Engineers | |
| dc.title | MFMA–Informer: A Short-Term Traffic Flow Prediction Model Incorporating Spatiotemporal Features | |
| dc.type | Journal Article | |
| dc.journal.volume | 152 | |
| dc.journal.issue | 1 | |
| dc.journal.title | Journal of Transportation Engineering, Part A: Systems | |
| dc.identifier.doi | 10.1061/JTEPBS.TEENG-9240 | |
| dc.journal.fristpage | 04025117-1 | |
| dc.journal.lastpage | 04025117-13 | |
| dc.page | 13 | |
| dc.tree | Journal of Transportation Engineering, Part A: Systems:;2026:;Volume ( 152 ):;issue: 001 | |
| dc.contenttype | Fulltext | |