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Academic Journal of Computing & Information Science, 2024, 7(1); doi: 10.25236/AJCIS.2024.070114.

Comprehensive Evaluation of Asphalt Pavement Performance in Hot and Humid Areas Based on Self-Organizing Map and Random Forest Algorithms

Author(s)

Qiao Sun1,2, Ideris Zakaria1

Corresponding Author:
Qiao Sun
Affiliation(s)

1Department of Civil Engineering, Infrastructure University, Kuala Lumpur, 430000, Malaysia

2College of Civil Engineering, Guangxi Electrical Polytechnic Institute, Nanning, 530000, China

Abstract

With the widespread application of asphalt pavement in highway construction in China, especially in hot and humid areas like Guangdong and Guangxi, this type of pavement faces challenges such as softening, rutting, and accelerated aging under high temperatures and moist conditions. Traditional evaluation models have limitations in these specific environments. This study proposes a new asphalt pavement performance evaluation model using Self-Organizing Map (SOM) and Random Forest (RF) algorithms, re-evaluating and optimizing the weight of pavement performance evaluation indicators based on actual data from 14 highways in hot and humid areas. Through cross-validation and case analysis, the new model not only excels in accurately reflecting the actual performance of asphalt pavement in hot and humid areas but also provides more effective decision support for local asphalt pavement maintenance and management.

Keywords

Humid and Hot Areas, Asphalt Pavement, Evaluation Model, SOM, RF

Cite This Paper

Qiao Sun, Ideris Zakaria. Comprehensive Evaluation of Asphalt Pavement Performance in Hot and Humid Areas Based on Self-Organizing Map and Random Forest Algorithms. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 1: 93-101. https://doi.org/10.25236/AJCIS.2024.070114.

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