On the interpretability of machine and deep learning techniques for predicting CBR of stabilized soil containing agro-industrial wastes
Crossref DOI link: https://doi.org/10.1038/s41598-025-30501-8
Published Online: 2026-01-09
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Ghorbanzadeh, Samira
Daei, Aydin
Armaghani, Danial Jahed
Payan, Meghdad
Text and Data Mining valid from 2026-01-09
Version of Record valid from 2026-01-13
Article History
Received: 30 March 2025
Accepted: 25 November 2025
First Online: 9 January 2026
Declarations
:
: The authors declare no competing interests.