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    Predicting errors in accident hotspots and investigating satiotemporal, weather, and behavioral factors using interpretable machine learning: An analysis of telematics big data. by Ali Golestani, Nazila Rezaei, Mohammad-Reza Malekpour, Naser Ahmadi, Seyed Mohammad-Navid Ataei, Sepehr Khosravi, Ayyoob Jafari, Saeid Shahraz, Farshad Farzadfar

    Published 2025-01-01
    “…SHAP values highlighted spatial-related variables, particularly the province of error and road type, as the most critical features for predicting errors in accident hotspots in Iran. …”
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    Exploring the Joint Influence of Built Environment Factors on Urban Rail Transit Peak-Hour Ridership Using DeepSeek by Zhuorui Wang, Xiaoyu Zheng, Fanyun Meng, Kang Wang, Xincheng Wu, Dexin Yu

    Published 2025-05-01
    “…We develop a 4D + N variable system for a more nuanced description of the built environment of the station area which includes density, diversity, design, destination accessibility, and station characteristics, leveraging multi-source data such as points of interest (POIs), road network data, housing prices, and population data. …”
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