Development of a Hybrid Machine Learning Model for Asphalt Pavement Temperature Prediction

Development of a Hybrid Machine Learning Model for Asphalt Pavement Temperature Prediction

Machine learning (ML) models are excellent alternative solutions to model complex engineering issues with high reliability and accuracy. This paper presents two extensively explored ensemble models for predicting asphalt pavement temperature, the Markov chain Monte Carlo (MCMC) and random forest (RF...

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Autores principales: Abdalrhman Abrahim Milad, Ibrahim Adwan, Sayf A. Majeed, Zubair Ahmed Memon, Munder Bilema, Hend Ali Omar, Maher G. M. Abdolrasol, Aliyu Usman, Nur Izzi Md Yusoff
Formato: article
Lenguaje:EN
Publicado: IEEE 2021
Materias:
Geophysical monitoring
hybridisation algorithms
machine learning
measurement
pavement temperature profile
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Acceso en línea:https://doaj.org/article/de693643f8ab4c7680d51218dff2d2d2
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https://doaj.org/article/de693643f8ab4c7680d51218dff2d2d2

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