Predicting the fracture mechanics responses of recycled asphalt mixes using machine learning-based algorithms: Application of CART algorithm and neural networks-Reference-Cited by-同舟云学术

Predicting the fracture mechanics responses of recycled asphalt mixes using machine learning-based algorithms: Application of CART algorithm and neural networks

Published:2022-12 Issue: Volume:276 Page:108791
ISSN:0013-7944
Container-title:Engineering Fracture Mechanics
language:en
Short-container-title:Engineering Fracture Mechanics

Author:

Motevalizadeh Seyed Mohsen,Kavussi Amir,Mollenhauer Konrad

Funder

Universität Kassel

Iran University of Science and Technology

Tarbiat Modares University

Bundesministerium für Bildung und Forschung

Ministry of Science Research and Technology

Publisher

Elsevier BV

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Reference38 articles.

1. Fracture and mechanical properties of water-based foam warm mix asphalt containing reclaimed asphalt pavement;Kavussi;Constr Build Mater,2021

2. Review of very high-content reclaimed asphalt use in plant-produced pavements: State of the art;Zaumanis;Int J Pavement Eng,2015

3. A review of the warm mix asphalt (WMA) technologies: Effects on thermo-mechanical and rheological properties;Behnood;J Clean Prod,2020

4. Evaluation of low-temperature cracking performance of asphalt pavements using Acoustic Emission: A review;Behnia;Appl Sci,2018

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Use of multivariate clustering analysis to investigate the physicochemical interactions in bitumen mastics using micromechanical modeling and FTIR spectroscopy;Construction and Building Materials;2024-10

2. Fatigue cracking prediction of RIOHTrack full-scale test track based on variable-order fractional Burgers model;Engineering Fracture Mechanics;2024-08

3. FTIR spectroscopy and multivariate discriminant analysis for classifying bituminous mastics: Exploring aging states and mastic composition;Construction and Building Materials;2024-08

4. Modelling of Marshall stability of polypropylene fibre reinforced asphalt concrete using support vector machine and artificial neural network;International Journal of Transportation Science and Technology;2024-08

5. Hydrogen production from plastic waste: A comprehensive simulation and machine learning study;International Journal of Hydrogen Energy;2024-03