Optimized prediction models for faulting failure of Jointed Plain concrete pavement using the metaheuristic optimization algorithms

•MOEA/D method has the best performance to select 17 features affecting faulting.•ANN- SAA with R2 value of 0.976 has been the best model for predicting faulting.•Pavement age, cumulative average precipitation, and elasticity modulus of concrete slab are the most important variables. This study aims...

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Vydáno v:	Construction & building materials Ročník 364; s. 129948
Hlavní autoři:	Ehsani, Mehrdad, Hamidian, Pouria, Hajikarimi, Pouria, Moghadas Nejad, Fereidoon
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 18.01.2023
Témata:	Artificial Neural Networks (ANN) Faulting Failure Feature Selection Jointed Plain Concrete Pavement Multi-objective Metaheuristic Optimization Algorithms Feature Selection Artificial Neural Networks (ANN) Faulting Failure Multi-objective Metaheuristic Optimization Algorithms Jointed Plain Concrete Pavement
ISSN:	0950-0618, 1879-0526
On-line přístup:	Získat plný text
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