Bituminous Mixtures Experimental Data Modeling Using a Hyperparameters-Optimized Machine Learning Approach

Bituminous Mixtures Experimental Data Modeling Using a Hyperparameters-Optimized Machine Learning Approach

This study introduces a machine learning approach based on Artificial Neural Networks (ANNs) for the prediction of Marshall test results, stiffness modulus and air voids data of different bituminous mixtures for road pavements. A novel approach for an objective and semi-automatic identification of t...

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Bibliographic Details
Main Authors: Matteo Miani, Matteo Dunnhofer, Fabio Rondinella, Evangelos Manthos, Jan Valentin, Christian Micheloni, Nicola Baldo
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Applied Sciences
Subjects:
bituminous mixtures
stiffness modulus
neural network
Bayesian optimization
Online Access:https://www.mdpi.com/2076-3417/11/24/11710

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