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keywords:(learning)

    Recent advances and prospects in hypersonic inlet design and intelligent optimization

    Ma, Yue / Guo, Mingming / Tian, Ye et al. | Elsevier | 2024
    Schlagwörter: Machine learning , Reinforcement learning

    A deep learning based traffic crash severity prediction framework

    Rahim, Md Adilur / Hassan, Hany M. | Elsevier | 2021
    Schlagwörter: Deep learning , Transfer learning

    Transferability improvement in short-term traffic prediction using stacked LSTM network

    Li, Junyi / Guo, Fangce / Sivakumar, Aruna et al. | Elsevier | 2021
    Schlagwörter: Transfer learning , Machine learning methods

    AIS data-driven ship trajectory prediction modelling and analysis based on machine learning and deep learning methods

    Li, Huanhuan / Jiao, Hang / Yang, Zaili | Elsevier | 2023
    Schlagwörter: Machine learning , Deep learning

    Hybrid deep reinforcement learning based eco-driving for low-level connected and automated vehicles along signalized corridors

    Guo, Qiangqiang / Angah, Ohay / Liu, Zhijun et al. | Elsevier | 2021
    Schlagwörter: Hybrid reinforcement learning , Deep Q-learning

    Relative motion guidance for near-rectilinear lunar orbits with path constraints via actor-critic reinforcement learning

    Scorsoglio, Andrea / Furfaro, Roberto / Linares, Richard et al. | Elsevier | 2022
    Schlagwörter: Machine learning , Reinforcement learning

    Highway crash detection and risk estimation using deep learning

    Huang, Tingting / Wang, Shuo / Sharma, Anuj | Elsevier | 2019
    Schlagwörter: Deep learning

    A novel passenger flow prediction model using deep learning methods

    Liu, Lijuan / Chen, Rung-Ching | Elsevier | 2017
    Schlagwörter: Deep learning

    A feature learning approach based on XGBoost for driving assessment and risk prediction

    Shi, Xiupeng / Wong, Yiik Diew / Li, Michael Zhi-Feng et al. | Elsevier | 2019
    Schlagwörter: Feature learning

    Developing and testing a hazard prediction task for novice drivers: A novel application of naturalistic driving videos

    Ehsani, Johnathon P. / Seymour, Karen E. / Chirles, Theresa et al. | Elsevier | 2020
    Schlagwörter: Learning

    A methodology to evaluate driving efficiency for professional drivers based on a maturity model

    Pozueco, Laura / Pañeda, Xabiel G. / Tuero, Alejandro G. et al. | Elsevier | 2017
    Schlagwörter: Learning evaluation methodology , Adaptive-learning

    An efficient realization of deep learning for traffic data imputation

    Duan, Yanjie / Lv, Yisheng / Liu, Yu-Liang et al. | Elsevier | 2016
    Schlagwörter: Deep learning

    ResLogit: A residual neural network logit model for data-driven choice modelling

    Wong, Melvin / Farooq, Bilal | Elsevier | 2021
    Schlagwörter: Deep learning , Machine learning

    Region-Aware Hierarchical Graph Contrastive Learning for Ride-Hailing Driver Profiling

    Chen, Kehua / Han, Jindong / Feng, Siyuan et al. | Elsevier | 2023
    Schlagwörter: Representation learning , Contrastive learning

    Real-world ride-hailing vehicle repositioning using deep reinforcement learning

    Jiao, Yan / Tang, Xiaocheng / Qin, Zhiwei (Tony) et al. | Elsevier | 2021
    Schlagwörter: Deep reinforcement learning

    Robust unsupervised learning of temporal dynamic vehicle-to-vehicle interactions

    Guha, Aritra / Lei, Rayleigh / Zhu, Jiacheng et al. | Elsevier | 2022
    Schlagwörter: Unsupervised learning

    Learning two-dimensional merging behaviour from vehicle trajectories with imitation learning

    Sun, Jie / Yang, Hai | Elsevier | 2024
    Schlagwörter: Imitation learning , Adversarial inverse reinforcement learning

    Lithological mapping of Nidar ophiolite complex, Ladakh using high-resolution data

    Chauhan, Mamta / Sur, Koyel / Chauhan, Prakash et al. | Elsevier | 2024
    Schlagwörter: Machine learning

    Data-efficient modeling for power consumption estimation of quadrotor operations using ensemble learning

    Dai, Wei / Zhang, Mingcheng / Low, Kin Huat | Elsevier | 2023
    Schlagwörter: Machine learning , Ensemble learning