Scalable machine learning framework for predicting critical links in urban networks

Scalable machine learning framework for predicting critical links in urban networks

Efficient identification of critical links in urban road networks is essential for optimizing traffic management, infrastructure planning, and resource allocation. Existing methods, such as simulation-based approaches, are computationally expensive and often impractical for large-scale networks. Thi...

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Bibliographic Details
Main Authors: Nourhan Bachir, Chamseddine Zaki, Hassan Harb, Roland Billen
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:Journal of Innovation & Knowledge
Subjects:
Link criticality
Urban traffic networks
Machine learning
Traffic management
Random Forest
Gradient Boosting
Online Access:http://www.sciencedirect.com/science/article/pii/S2444569X25000654
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