Cracking is a common pavement distress and has a significant impact on structural integrity, traffic safety, and maintenance strategies throughout the entire pavement life cycle. This study presents an improved YOLOv8s-based framework that can effectively and accurately detect asphalt pavement cracks. The proposed mo...
Zong-Kai Zhu, Xin-Yu Zuo, Ahmed D. Almutairi et al.· Scientific Reports· 0 citations
With the growing complexity and variability of the operational environment of asphalt pavements and the continuous increase in traffic loads, traditional pavement performance prediction models cannot accurately depict the nonlinear degradation process of pavement performance with the passage of time. Therefore, a novel...
Xinyu Zuo, Yufan Du, Guangsheng Zeng et al.· Materials· 0 citations
Alkali-activated recycled aggregate concrete (AARAC) offers a sustainable alternative to traditional concrete but suffers from complex, non-linear mechanical behavior that challenges conventional prediction methods. This study develops and compares five machine learning models, linear regression (LR), M5P, Random Fores...
Ahmed D. Almutairi, A. A. Al Sayed· Buildings· 0 citations
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