Multi-location Traffic Flow Dataset: Stockton and Oakland California

This dataset supports the research detailed in "A Hybrid Deep Learning Approach with GEH-based Loss Function and Evaluation Metric for Multi-location Traffic Flow Forecasting" containing traffic flow measurements from Stockton and Oakland, California. The dataset is organized into four sub-folders: 'Oakland-raw', 'Oakland-processed', 'Stockton-raw', and 'Stockton-processed'. The raw data folders ('Oakland-raw' and 'Stockton-raw') include the initial traffic measurements as collected directly from traffic sensors, providing a granular view of traffic patterns without any modifications. The processed data folders ('Oakland-processed' and 'Stockton-processed') contain data that has been cleaned and structured, making it more suitable for analytical tasks and modeling purposes.