Forecasting transport flows using big data and machine learning technology

Abstract

Efficient management of urban transportation is crucial for addressing the growing challenges posed by increasing traffic and population. In this context, the utilization of big data and intelligent systems has become paramount. This paper introduces a comprehensive approach to traffic flow management at a key intersection in Tashkent, capitalizing on the integration of big data analytics and predictive model.

Keywords

• big data
• machine learning
• crisp-dm
• its
• traffic flow
• gradient boosting regressor
• intersection
• correlation
• regression