The impact of data noise on permanent deformation behaviour of asphalt concrete mixtures-Reference-Cited by-同舟云学术

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The impact of data noise on permanent deformation behaviour of asphalt concrete mixtures

Published:2018-11-27 Issue:12 Volume:21 Page:1470-1481
ISSN:1029-8436
Container-title:International Journal of Pavement Engineering
language:en
Short-container-title:International Journal of Pavement Engineering

Author:

Ali Yasir¹^ORCID,Irfan Muhammad²^ORCID,Hussain Etikaf³

Affiliation:

1. National Institute of Transportation, National University of Sciences & Technology (NUST), Risalpur, Pakistan

2. Military College of Engineering (MCE), National University of Sciences & Technology (NUST), Risalpur, Pakistan

3. Civil Engineering Department, NED University of Engineering and Technology, Karachi, Pakistan

Publisher

Informa UK Limited

Subject

Mechanics of Materials,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10298436.2018.1549324

Reference42 articles.

1. Formulation of flow number of asphalt mixes using a hybrid computational method

2. Empirical Correlation of Permanent Deformation Tests for Evaluating the Rutting Response of Conventional Asphaltic Concrete Mixtures

3. Permanent deformation prediction of asphalt concrete mixtures – A synthesis to explore a rational approach

Cited by 6 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. Slope deformation prediction based on noise reduction and deep learning: a point prediction and probability analysis method;Frontiers in Earth Science;2024-05-27

2. Prediction of Glass Chemical Composition and Type Identification Based on Machine Learning Algorithms;Applied Sciences;2024-05-09

3. Development of double-tangent method to determine transition points of three-stage permanent deformation of asphalt mixture;Materials and Structures;2022-09-16

4. Developing fragility curves for asphalt mixture to assess the uncertainty of the permanent deformation performance;Construction and Building Materials;2021-12

5. Alternative Approach for Predicting the Phase Angle Characteristics of Asphalt Concrete Mixtures Based on Recurrent Neural Networks;Journal of Materials in Civil Engineering;2021-09

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