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dc.contributor.authorCao, Can
dc.contributor.authorLiu, Yancheng
dc.contributor.authorJiao, Xiaolei
dc.contributor.authorLi, Yiming
dc.contributor.authorXu, Yongli
dc.date.accessioned2026-08-20T11:42:27Z
dc.date.available2026-08-20T11:42:27Z
dc.date.copyright2026/01/31
dc.date.issued2026
dc.identifier.otherJMCEE7.MTENG-21647.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312564
dc.description.abstractAbstractAggregate 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.publisherAmerican Society of Civil Engineers
dc.titlePredicting Aggregate Gradation Based on Pavement Surface Image Features Using Random Forest and Multilayer Perceptron Integrated Model
dc.typeJournal Article
dc.journal.volume38
dc.journal.issue4
dc.journal.titleJournal of Materials in Civil Engineering
dc.identifier.doi10.1061/JMCEE7.MTENG-21647
dc.journal.fristpage04026050-1
dc.journal.lastpage04026050-11
dc.page11
dc.treeJournal of Materials in Civil Engineering:;2026:;Volume ( 038 ):;issue: 004
dc.contenttypeFulltext


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