| dc.contributor.author | Cao, Can | |
| dc.contributor.author | Liu, Yancheng | |
| dc.contributor.author | Jiao, Xiaolei | |
| dc.contributor.author | Li, Yiming | |
| dc.contributor.author | Xu, Yongli | |
| dc.date.accessioned | 2026-08-20T11:42:27Z | |
| dc.date.available | 2026-08-20T11:42:27Z | |
| dc.date.copyright | 2026/01/31 | |
| dc.date.issued | 2026 | |
| dc.identifier.other | JMCEE7.MTENG-21647.pdf | |
| dc.identifier.uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4312564 | |
| dc.description.abstract | AbstractAggregate gradation significantly impacts the road performance of asphalt pavement.
However, current detection methods are often inefficient, destroying the pavement
structure, and do not allow for quick real-time detection. The advancement of ...Practical ApplicationsIn the quality control of asphalt pavement construction, aggregate gradation detection
represents a core mandatory inspection. However, traditional sieving tests are plagued
by drawbacks such as lengthy cycles and the inability to ... | |
| dc.publisher | American Society of Civil Engineers | |
| dc.title | Predicting Aggregate Gradation Based on Pavement Surface Image Features Using Random Forest and Multilayer Perceptron Integrated Model | |
| dc.type | Journal Article | |
| dc.journal.volume | 38 | |
| dc.journal.issue | 4 | |
| dc.journal.title | Journal of Materials in Civil Engineering | |
| dc.identifier.doi | 10.1061/JMCEE7.MTENG-21647 | |
| dc.journal.fristpage | 04026050-1 | |
| dc.journal.lastpage | 04026050-11 | |
| dc.page | 11 | |
| dc.tree | Journal of Materials in Civil Engineering:;2026:;Volume ( 038 ):;issue: 004 | |
| dc.contenttype | Fulltext | |