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

• Main Authors: Milad, A.A., Adwan, I., Majeed, S.A., Memon, Z.A., Bilema, M., Omar, H.A., Abdolrasol, M.G.M., Usman, A., Yusoff, N.I.M.
• Format: Article
• Published: Institute of Electrical and Electronics Engineers Inc. 2021
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120050406&doi=10.1109%2fACCESS.2021.3129979&partnerID=40&md5=234343c6590d335875edd8bcad344ef6; http://eprints.utp.edu.my/29371/

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...