Synonyme wurden verwendet für: learning  deep learning
Suche ohne Synonyme: keywords:( deep learning)

21–38 von 38 Ergebnissen
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    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

    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

    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

    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

    Price incentive strategy for the E-scooter sharing service using deep reinforcement learning

    Yun, Hyunsoo / Kim, Eui-Jin / Ham, Seung Woo et al. | Taylor & Francis Verlag | 2024
    Schlagwörter: Deep reinforcement 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

    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

    Traffic sign extraction using deep hierarchical feature learning and mobile light detection and ranging (LiDAR) data on rural highways

    Gouda, Maged / Epp, Alexander / Tilroe, Rowan et al. | Taylor & Francis Verlag | 2023
    Schlagwörter: Deep learning

    Collision-avoidance under COLREGS for unmanned surface vehicles via deep reinforcement learning

    Ma, Yong / Zhao, Yujiao / Wang, Yulong et al. | Taylor & Francis Verlag | 2020
    Schlagwörter: deep reinforcement learning

    Two-stage procedure for transportation mode detection based on sighting data

    Chen, Huey-Kuo / Ho, Hsiao-Ching / Wu, Luo-Yu et al. | Taylor & Francis Verlag | 2024
    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

    PLDA in i-vector based underwater acoustic signals classification

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

    Parameter tuning of EV drivers' charging behavioural model using machine learning techniques

    Fotouhi, Zohreh / Narimani, Hamed / Hashemi, Massoud Reza | Taylor & Francis Verlag | 2023
    Schlagwörter: Deep reinforcement learning (DRL)

    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

    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

    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

    Discharge control policy based on density and speed for deep Q-learning adaptive traffic signal

    Ahmed, Muaid Abdulkareem Alnazir / Khoo, Hooi Ling / Ng, Oon-Ee | Taylor & Francis Verlag | 2023
    Schlagwörter: deep Q-learning