What is it about?
The effective prediction of rutting on asphalt pavement is a difficult problem in industrial field. How to accurately characterize the rutting evolution law is an important research topic in the industry. This paper obtains the characteristic factors related to asphalt road rutting through machine learning, and uses the RIOHTrack full-scale track data to carry out the simulation research on the characteristic factors to the unknown domain data through machine learning, and obtains the corresponding prediction results. In this paper, by comparing the mechanical model and the machine learning model, combined with different division of data set, the influence of eigenvalues on generalization ability of asphalt rutting prediction model is revealed.
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Why is it important?
This paper analyzes and demonstrates the influence of eigenvalues on the generalization ability of the model.
Perspectives
It has certain reference significance for the study of rutting on asphalt pavement.
bo kou
Southeast University
Read the Original
This page is a summary of: Generalization ability of rutting prediction model for asphalt pavement based on RIOHTrack full-scale track, April 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3664934.3664951.
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