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contributor authorAwuku, Bright
contributor authorAsa, Eric
date accessioned2026-08-20T11:59:31Z
date available2026-08-20T11:59:31Z
date copyright2026/04/27
date issued2026
identifier otherJPCFEV.CFENG-5198.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312944
description abstractAbstractTransportation agencies rely on accurate predictions of bridge substructure conditions for planning, resource allocation, and ensuring the safety of their infrastructure. Traditional deterioration models fail to adequately capture the complex ...
publisherAmerican Society of Civil Engineers
titleGenetic Feature Selection and Multistage Deep Learning for Bridge Substructure Condition Prediction
typeJournal Article
journal volume40
journal issue4
journal titleJournal of Performance of Constructed Facilities
identifier doi10.1061/JPCFEV.CFENG-5198
journal fristpage04026018-1
journal lastpage04026018-18
page18
treeJournal of Performance of Constructed Facilities:;2026:;Volume ( 040 ):;issue: 004
contenttypeFulltext


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