Automated, economical, and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization
- DOI
- 10.1016/j.jtte.2023.10.002
- Published
- 06
- Container
- Journal of Traffic and Transportation Engineering (English ed. Online)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.jtte.2023.10.002,
title = {Automated, economical, and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization},
author = {Jian Liu and Fangyu Liu and Linbing Wang},
year = {2024},
journal = {Journal of Traffic and Transportation Engineering (English ed. Online)},
doi = {10.1016/j.jtte.2023.10.002},
url = {https://doi.org/10.1016/j.jtte.2023.10.002}
}RIS
TY - JOUR TI - Automated, economical, and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization AU - Jian Liu AU - Fangyu Liu AU - Linbing Wang PY - 2024 JO - Journal of Traffic and Transportation Engineering (English ed. Online) DO - 10.1016/j.jtte.2023.10.002 UR - https://doi.org/10.1016/j.jtte.2023.10.002 ER -
APA
Liu, J., Liu, F., & Wang, L. (2024). Automated, economical, and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization. Journal of Traffic and Transportation Engineering (English ed. Online). https://doi.org/10.1016/j.jtte.2023.10.002
Source records
- doaj · retrieved 2026-09-25T08:47:33.797Z