Cargando…
Adaboost Algorithm in Artificial Intelligence for Optimizing the IRI Prediction Accuracy of Asphalt Concrete Pavement
The international roughness index (IRI) for roads is a crucial pavement design criterion in the Mechanistic-Empirical Pavement Design Guide (MEPDG). However, studies have shown that the IRI transfer function in the MEPDG is simply a linear combination of road parameters, so it cannot provide accurat...
Autores principales: | Wang, Changbai, Xu, Shuzhan, Yang, Junxin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434306/ https://www.ncbi.nlm.nih.gov/pubmed/34502573 http://dx.doi.org/10.3390/s21175682 |
Ejemplares similares
-
Fatigue Properties and Its Prediction of Polymer Concrete for the Repair of Asphalt Pavements
por: Ren, Senzhi, et al.
Publicado: (2022) -
Asphalt-Cement Concretes with Reclaimed Asphalt Pavement and Rubber Powder from Recycled Tire
por: Kukiełka, Jerzy, et al.
Publicado: (2021) -
Machine learning approaches for predicting Cracking Tolerance Index (CTIndex) of asphalt concrete containing reclaimed asphalt pavement
por: Nguyen, Lan Ngoc, et al.
Publicado: (2023) -
Electrode Layout Optimization and Numerical Simulation of Cast Conductive Asphalt Concrete Steel Bridge Deck Pavement
por: Li, Zhenxia, et al.
Publicado: (2022) -
Interlaminar Bonding Properties on Cement Concrete Deck and Phosphorous Slag Asphalt Pavement
por: Qian, Guoping, et al.
Publicado: (2019)