z-logo
open-access-imgOpen Access
Road Pavement Asphalt Concretes for Thin Wearing Layers: A Machine Learning Approach towards Stiffness Modulus and Volumetric Properties Prediction
Author(s) -
Nicola Baldo,
Matteo Miani,
Fabio Rondinella,
Evangelos Manthos,
Jan Valentin
Publication year - 2022
Publication title -
periodica polytechnica civil engineering
Language(s) - English
Resource type - Journals
eISSN - 1587-3773
pISSN - 0553-6626
DOI - 10.3311/ppci.19996
Subject(s) - hyperparameter , asphalt , generalization , artificial neural network , stiffness , computer science , feature (linguistics) , set (abstract data type) , asphalt pavement , asphalt concrete , artificial intelligence , machine learning , structural engineering , materials science , engineering , composite material , mathematics , mathematical analysis , linguistics , philosophy , programming language

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom