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keywords:("Deep 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

    A deep learning traffic flow prediction framework based on multi-channel graph convolution

    Zhao, Yuanmeng / Cao, Jie / Zhang, Hong et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning

    Artificial intelligence for traffic signal control based solely on video images

    Jeon, Hyunjeong / Lee, Jincheol / Sohn, Keemin | Taylor & Francis Verlag | 2018
    Schlagwörter: deep learning

    Characterizing parking systems from sensor data through a data-driven approach

    Arjona Martinez, Jamie / Linares, Maria Paz / Casanovas, Josep | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning

    Convolutional neural network for detecting railway fastener defects using a developed 3D laser system

    Zhan, You / Dai, Xianxing / Yang, Enhui et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning

    Deep Architecture for Citywide Travel Time Estimation Incorporating Contextual Information

    Tang, Kun / Chen, Shuyan / Khattak, Aemal J. et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning

    Deep machine learning for structural health monitoring on ship hulls using acoustic emission method

    Karvelis, Petros / Georgoulas, George / Kappatos, Vassilios et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: deep 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

    Development of LSTM-MLR hybrid model for radar detector missing and outlier traffic volume correction

    Kim, Dohoon / Kim, Eungcheol | Taylor & Francis Verlag | 2023
    Schlagwörter: deep-learning

    DLW-Net model for traffic flow prediction under adverse weather

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

    Electric vehicle charging demand forecasting using deep learning model

    Yi, Zhiyan / Liu, Xiaoyue Cathy / Wei, Ran et al. | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning

    Fast prediction of turbine energy acquisition capacity under combined action of wave and current based on digital twin method

    Cao, Yu / Tang, Xiaobo / Zhang, Tao et al. | Taylor & Francis Verlag | 2024
    Schlagwörter: deep learning

    Forecasting citywide short-term turning traffic flow at intersections using an attention-based spatiotemporal deep learning model

    Jia, Tao / Cai, Chenxi | Taylor & Francis Verlag | 2023
    Schlagwörter: Deep learning

    Fusion attention mechanism bidirectional LSTM for short-term traffic flow prediction

    Li, Zhihong / Xu, Han / Gao, Xiuli et al. | Taylor & Francis Verlag | 2024
    Schlagwörter: deep learning

    GPS-based citywide traffic congestion forecasting using CNN-RNN and C3D hybrid model

    Guo, Jingqiu / Liu, Yangzexi / Yang, Qingyan (Ken) et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning

    Graph attention temporal convolutional network for traffic speed forecasting on road networks

    Zhang, Ke / He, Fang / Zhang, Zhengchao et al. | Taylor & Francis Verlag | 2021
    Schlagwörter: deep learning

    Hybrid deep learning models for short-term demand forecasting of online car-hailing considering multiple factors

    Li, Siteng / Yang, Hang / Cheng, Rongjun et al. | Taylor & Francis Verlag | 2024
    Schlagwörter: deep learning

    Inferring safety critical events from vehicle kinematics in naturalistic driving environment: Application of deep learning Algorithms

    Khattak, Zulqarnain H. / Rios-Torres, Jackeline / Fontaine, Michael D. et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: deep learning

    Joint learning of video images and physiological signals for lane-changing behavior prediction

    Gao, Jun / Yi, Jiangang / Murphey, Yi Lu | Taylor & Francis Verlag | 2022
    Schlagwörter: deep learning

    PLDA in i-vector based underwater acoustic signals classification

    Song, Yongqiang / Liu, Feng / Shen, Tongsheng | Taylor & Francis Verlag | 2024
    Schlagwörter: Deep learning

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