Enhancing Pavement Design Using Machine Learning and Social Network Analysis for Sustainable Environmental Impact
Autour(s)
- Bing Pan, Lixuan Zhang, Chang Li, Don Chen, Lee Chen
Abstract
Pavement design is an essential aspect of transportation infrastructure that significantly affects the environment. Traditional pavement design methods rely on expert knowledge and experience, which can lead to suboptimal designs and negative environmental impacts. In this article, we propose an approach that combines machine learning and social network analysis to improve pavement design and its environmental impact. Our approach uses machine learning to analyze pavement performance data and social network analysis to identify the interrelationships among various factors affecting pavement design. The result is a comprehensive analysis of the impact of pavement design on the environment and strategies for improving its sustainability.