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    What Lies behind Idle Connection Time in Fast-Charging Public Stations: Evidence from Changshu, China

    Zhou, Xizhen / Ding, Xueqi / Ji, Yanjie | ASCE | 2024
    Schlagwörter: Machine learning

    Urban Road Traffic State Level Classification Based on Dynamic Ensemble Learning Algorithm

    Liu, Qingchao / Cai, Yingfeng / Jiang, Haobin et al. | ASCE | 2018
    Schlagwörter: dynamic ensemble learning

    Unsupervised Approach to Investigate Urban Traffic Crashes Based on Crash Unit, Crash Severity, and Manner of Collision

    Maniei, Farzin / Mattingly, Stephen P. | ASCE | 2024
    Schlagwörter: Unsupervised learning

    Traffic Speed Prediction for Urban Arterial Roads Using Deep Neural Networks

    Adu-Gyamfi, Yaw / Zhao, Mo | ASCE | 2018
    Schlagwörter: Deep learning

    Traffic Order Analysis of Intersection Entrance Based on Aggressive Driving Behavior Data Using CatBoost and SHAP

    Zhao, Xiaohua / Qi, Hang / Yao, Ying et al. | ASCE | 2023
    Schlagwörter: Machine learning

    Traffic Congestion Prediction Based on Long-Short Term Memory Neural Network Models

    Chen, Min / Yu, Guizhen / Chen, Peng et al. | ASCE | 2018
    Schlagwörter: deep learning theory

    Suppression of Roll Oscillations of a Canard-Configuration Model Using Fluid Effector and Reinforcement Learning

    Dong, Yizhang / Shi, Zhiwei / Chen, Kun et al. | ASCE | 2023
    Schlagwörter: Reinforcement learning

    Short-Time Bus Route Passenger Flow Prediction Based on a Secondary Decomposition Integration Method

    Li, Yuanping / Ma, Changxi | ASCE | 2023
    Schlagwörter: Kernel extreme learning machine (KELM)

    Self-Supervised Deep Learning Framework for Anomaly Detection in Traffic Data

    Morris, Clint / Yang, Jidong J. / Chorzepa, Mi Geum et al. | ASCE | 2022
    Schlagwörter: Self-supervised deep learning

    Real-Time Optimization of Urban Rail Transit Train Scheduling via Advantage Actor–Critic Deep Reinforcement Learning

    Wen, Longhui / Zhou, Wei / Liu, Jiajun et al. | ASCE | 2024
    Schlagwörter: Deep reinforcement learning

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