Crack damage prediction of asphalt pavement based on tire noise: A comparison of machine learning algorithms

Author:

Li Huixia,Nyirandayisabye RithaORCID,Dong Qiming,Niyirora Rosette,Hakuzweyezu Theogene,Zardari Irshad Ali,Nkinahamira François

Publisher

Elsevier BV

Reference76 articles.

1. An artificial intelligence method for asphalt pavement pothole detection using least squares support vector machine and neural network with steerable filter-based feature extraction;Hoang;Adv. Civ. Eng.,2018

2. Prediction of pavement fatigue cracking at an accelerated testing section using asphalt mixture performance tests;Ozer;Int. J. Pavement Eng.,2018

3. An ANN model to correlate roughness and structural performance in asphalt pavements;Sollazzo;Constr. Build. Mater.,2017

4. Measurement of noise from road surface using dynamic method;Křivánek;Trans. Transp. Sci.,2013

5. The influence of tyres on the use of the CPX method for evaluating the effectiveness of a noise mitigation action based on low-noise road surfaces;Licitra;Transp. Res. Part D. Transp. Environ.,2017

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