Can I read Machine Learning for Urban Traffic Congestion on EtoBox?

Machine Learning for Urban Traffic Congestion by cansincinel is a document available to read on EtoBox.

What is Machine Learning for Urban Traffic Congestion about?

The document presents a study on predictive modeling of intersection congestion using machine learning to enhance sustainable urban traffic management. It introduces a novel feature selection method, Dual Importance Intersection Feature Selection (DIFS), and evaluates various machine learning models, with Categorical Boosting (CatBoost) achieving the highest performance metrics. The findings suggest that integrating capacity-based congestion labeling and robust feature selection can significantly improve re

Author

cansincinel

Language

EN