Machine learning techniques to estimate the degree of binder activity of reclaimed asphalt pavement

Autor: Ramon Botella, Davide Lo Presti, Kamilla Vasconcelos, Kinga Bernatowicz, Adriana H. Martínez, Rodrigo Miró, Luciano Specht, Edith Arámbula Mercado, Gustavo Menegusso Pires, Emiliano Pasquini, Chibuike Ogbo, Francesco Preti, Marco Pasetto, Ana Jiménez del Barco Carrión, Antonio Roberto, Marko Orešković, Kranthi K. Kuna, Gurunath Guduru, Amy Epps Martin, Alan Carter, Gaspare Giancontieri, Ahmed Abed, Eshan Dave, Gabrielle Tebaldi

Publikováno v: Scientia
Digibug. Repositorio Institucional de la Universidad de Granada
instname
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Materials and Structures

Part of this research was funded by the project RTI2018-096224-J-I00 that has been cofounded by the Spanish Ministry of Science and Innovation, inside the National Program for Fostering Excellence in Scientific and Technical Research, National Subpro

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::320b0479aad50c189aaadb83d77d80ad
https://hdl.handle.net/11351/8306