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Build it up

You are kindly requested to revise your manuscript and submit the updated version to PFDM 2025 before 15-06-2025.

 

Below, you will find all relevant review comments from:

​

  • Scientific Committee,

  • Track Leaders,

  • The Editorial Team
     

Please consider these carefully in preparing your revised manuscript.Once your revisions are complete, you may submit the updated version using the submission link provided at the bottom of this page.We appreciate your contributions and look forward to receiving your revised manuscript.

Leveraging Machine Learning to Predict Moisture Damage in Asphalt Mixtures with RAP

Reviewer's feedback:

This paper presents a well-organized application of machine learning models to predict moisture susceptibility in RAP-containing asphalt mixtures. A brief discussion on data preprocessing techniques, such as variable transformation, would further strengthen the robustness of the modeling approach. The authors are also advised to ensure that the manuscript length complies with the formatting and submission requirements of the PFDM conference.

Editorial Decision for Conference Proceedings:

No additinional comments!

Track Leader’s Comments (if any):

Please note that some of the track leader’s comments are intended as feedback for future improvements

Thanks for the paper and we look forward to your presentation. It is recommended to talk insight about the transportation infrastructure, especially its contents and requirements along with ITS.

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