Predicting Marshall stability and flow parameters in asphalt pavements using explainable machine-learning models

被引：0
|
作者：
Asi, Ibrahim [1 ]
Alhadidi, Yusra I. [2 ,3 ]
Alhadidi, Taqwa I. [1 ]
机构：
[1] Civil Engineering Department, Al-Ahliyya Amman University, Amman,19328, Jordan
[2] Ph.D. Candidate, Transportation Engineering Researcher, Illinois Center for Transportation 1611 Titan Drive, Rantoul,IL,61866, United States
[3] Research Fellow AlBalqa'a Applied University, Salt, Jordan
来源：
Transportation Engineering | 2024年 / 18卷
关键词：
Compendex;
D O I：
10.1016/j.treng.2024.100282
中图分类号：
学科分类号：
摘要：
Adversarial machine learning - Asphalt - Prediction models - Regression analysis
引用
下载
收藏
相关论文
共 50 条
  • [1] Prediction of Marshall Stability and Marshall Flow of Asphalt Pavements Using Supervised Machine Learning Algorithms
    Gul, Muhammad Aniq
    Islam, Md Kamrul
    Awan, Hamad Hassan
    Sohail, Muhammad
    Al Fuhaid, Abdulrahman Fahad
    Arifuzzaman, Md
    Qureshi, Hisham Jahangir
    SYMMETRY-BASEL, 2022, 14 (11):
  • [2] Predicting Marshall Flow and Marshall Stability of Asphalt Pavements Using Multi Expression Programming
    Awan, Hamad Hassan
    Hussain, Arshad
    Javed, Muhammad Faisal
    Qiu, Yanjun
    Alrowais, Raid
    Mohamed, Abdeliazim Mustafa
    Fathi, Dina
    Alzahrani, Abdullah Mossa
    BUILDINGS, 2022, 12 (03)
  • [3] Predicting Marshall Stability of Carbon Fiber-Reinforced Asphalt Concrete Using Machine Learning Techniques
    Ankita Upadhya
    M. S. Thakur
    Parveen Sihag
    International Journal of Pavement Research and Technology, 2024, 17 : 102 - 122
  • [4] Predicting Marshall Stability of Carbon Fiber-Reinforced Asphalt Concrete Using Machine Learning Techniques
    Upadhya, Ankita
    Thakur, M. S.
    Sihag, Parveen
    INTERNATIONAL JOURNAL OF PAVEMENT RESEARCH AND TECHNOLOGY, 2024, 17 (01) : 102 - 122
  • [5] Insight into glacio-hydrologicalprocesses using explainable machine-learning (XAI) models
    Hao, Huiqing
    Hao, Yonghong
    Li, Zhongqin
    Qi, Cuiting
    Wang, Qi
    Zhang, Ming
    Liu, Yan
    Liu, Qi
    Yeh, Tian-Chyi Jim
    JOURNAL OF HYDROLOGY, 2024, 634
  • [6] EXPLAINABLE MACHINE-LEARNING FOR PREDICTING PREOPERATIVE FRAILTY PHENOTYPE USING ELECTRONIC HEALTH RECORDS
    Mardini, Mamoun
    Price, Catherine
    Tighe, Patrick
    Manini, Todd
    INNOVATION IN AGING, 2022, 6 : 564 - 564
  • [7] Establishing a Classification System for Predicting Flow-Limiting Dissection After Balloon Angioplasty Using Explainable Machine-Learning Models: A Multicenter Retrospective Cohort Study
    Hou, Xinhuang
    Xu, Shuguo
    Lin, Tong
    Liu, Liang
    Guo, Pingfan
    Cai, Fanggang
    Zhang, Jinchi
    Lin, Jun
    Lai, Xiaoling
    Li, Wanglong
    Dai, Yiquan
    JOURNAL OF ENDOVASCULAR THERAPY, 2024,
  • [8] Comparison of machine-learning models for predicting short-term building heating load using operational parameters
    Zhou, Yong
    Liu, Yanfeng
    Wang, Dengjia
    Liu, Xiaojun
    ENERGY AND BUILDINGS, 2021, 253
  • [9] Predicting power consumption of drones using explainable optimized mathematical and machine learning models
    Eman I. Abd El-Latif
    Mohamed El-dosuky
    The Journal of Supercomputing, 81 (5)
  • [10] Development and validation of explainable machine-learning models for carotid atherosclerosis early screening
    Yun, Ke
    He, Tao
    Zhen, Shi
    Quan, Meihui
    Yang, Xiaotao
    Man, Dongliang
    Zhang, Shuang
    Wang, Wei
    Han, Xiaoxu
    JOURNAL OF TRANSLATIONAL MEDICINE, 2023, 21 (01)
12345