Physics-guided neural network for predicting asphalt mixture rutting with balanced accuracy, stability and rationality-Reference-Cited by-同舟云学术

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Physics-guided neural network for predicting asphalt mixture rutting with balanced accuracy, stability and rationality

Published:2024-04 Issue: Volume:172 Page:106085
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Deng Yong,Wang Haifeng^ORCID,Shi Xianming^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference44 articles.

1. Standard method of test for Hamburg wheel-track testing of compacted asphalt mixtures;AASHTO,2022

2. Standard method of test for determining the flexural creep stiffness of asphalt binder using the Bending Beam Rheometer (BBR);AASHTO,2022

3. Standard specification for superpave volumetric mix design;AASHTO,2022

4. Standard method of test for flash point of asphalt binder by cleveland open cup;AASHTO,2022

5. Standard method of test for effect of heat and air on a moving film of asphalt binder (Rolling thin-film oven test);AASHTO,2022

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. DualFluidNet: An attention-based dual-pipeline network for fluid simulation;Neural Networks;2024-09

2. Gradient boosting decision trees to study laboratory and field performance in pavement management;Computer-Aided Civil and Infrastructure Engineering;2024-08-17

3. A Machine Learning based approach to predict road rutting considering uncertainty;Case Studies in Construction Materials;2024-07

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