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81–100 von 204 Ergebnissen
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    Predicting and explaining severity of road accident using artificial intelligence techniques, SHAP and feature analysis

    Panda, Chakradhara / Mishra, Alok Kumar / Dash, Aruna Kumar et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: machine learning

    Using reinforcement learning to minimize taxi idle times

    O’Keeffe, Kevin / Anklesaria, Sam / Santi, Paolo et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: machine learning , reinforcement learning

    Learning through policy transfer? Reviewing a decade of scholarship for the field of transport

    Freier Zugriff
    Glaser, Meredith / Bertolini, Luca / te Brömmelstroet, Marco et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: policy learning , learning

    A cold-start-free reinforcement learning approach for traffic signal control

    Xiao, Nan / Yu, Liang / Yu, Jinqiang et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning , reinforcement learning

    Performance evaluation of mode choice models under balanced and imbalanced data assumptions

    Rezaei, Shahrbanoo / Khojandi, Anahita / Haque, Antora Mohsena et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: imbalanced learning , machine learning

    Detecting transportation modes using smartphone data and GIS information: evaluating alternative algorithms for an integrated smartphone-based travel diary imputation

    Liu, Yicong / Miller, Eric / Habib, Khandker Nurul | Taylor & Francis Verlag | 2022
    Schlagwörter: machine learning , tree-based ensemble learning

    Shipping market forecasting by forecast combination mechanism

    Gao, Ruobin / Liu, Jiahui / Du, Liang et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: machine learning

    A data-driven lane-changing behavior detection system based on sequence learning

    Gao, Jun / Murphey, Yi Lu / Yi, Jiangang et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: sequence learning

    Microscopic modeling of cyclists on off-street paths: a stochastic imitation learning approach

    Mohammed, Hossameldin / Sayed, Tarek / Bigazzi, Alexander | Taylor & Francis Verlag | 2022
    Schlagwörter: machine learning

    Station-level short-term demand forecast of carsharing system via station-embedding-based hybrid neural network

    Zhao, Feifei / Wang, Weiping / Sun, Huijun et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: Machine learning

    Machine learning techniques to predict reactionary delays and other associated key performance indicators on British railway network

    Taleongpong, Panukorn / Hu, Simon / Jiang, Zhoutong et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: machine learning

    Real-time traffic incident detection based on a hybrid deep learning model

    Li, Linchao / Lin, Yi / Du, Bowen et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning

    Reinforcement learning-enabled genetic algorithm for school bus scheduling

    Köksal Ahmed, Eda / Li, Zengxiang / Veeravalli, Bharadwaj et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: reinforcement learning

    Framework for development of the Scheduler for Activities, Locations, and Travel (SALT) model

    Hesam Hafezi, Mohammad / Sultana Daisy, Naznin / Millward, Hugh et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: machine-learning

    Integrating data-driven and simulation models to predict traffic state affected by road incidents

    Shafiei, Sajjad / Mihăiţă, Adriana-Simona / Nguyen, Hoang et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: machine learning

    Assessing influential factors for lane change behavior using full real-world vehicle-by-vehicle data

    Basso, Franco / Cifuentes, Álvaro / Cuevas-Pavincich, Francisca et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: Interpretable Machine Learning

    DLW-Net model for traffic flow prediction under adverse weather

    Yao, Ronghan / Zhang, Wensong / Long, Meng | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning

    Prediction of pedestrians’ wait-or-go decision using trajectory data based on gradient boosting decision tree

    Xin, Xiuying / Jia, Ning / Ling, Shuai et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: ensemble learning

    Estimating cycle-level real-time traffic movements at signalized intersections

    Mahmoud, Nada / Abdel-Aty, Mohamed / Cai, Qing et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: machine learning

    Development of a novel engine power model to estimate heavy-duty truck fuel consumption

    Kan, Yuheng / Liu, Hao / Lu, Xiaoyun et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning