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keywords:(learning)

    Uncertainty quantification of aeroelastic wings flutter using an optimized machine learning approach

    Rezaei, Mohsen / Shirazi, Kourosh H / H Khodaparast, Hamed | SAGE Publications | 2022
    Schlagwörter: machine learning

    Tactical driving decisions of unmanned ground vehicles in complex highway environments: A deep reinforcement learning approach

    Wang, Huanjie / Yuan, Shihua / Guo, Mengyu et al. | SAGE Publications | 2021
    Schlagwörter: deep reinforcement learning

    Study of the influence of multiple factors on the boundary layer of a high-lift LPT with the RBF-GA method

    Sun, Shuang / Huang, Zhen / Kang, Jinhui et al. | SAGE Publications | 2024
    Schlagwörter: machine learning

    Strategy for on-orbit space object classification using deep learning

    Lim, Seongmin / Kim, Jin-Hyung / Kim, Hae-Dong | SAGE Publications | 2021
    Schlagwörter: Deep learning

    Soft one-class extreme learning machine for turboshaft engine fault detection

    Zhao, Yong-Ping / Huang, Gong | SAGE Publications | 2022
    Schlagwörter: machine learning , one-class extreme learning machine

    SMART on-board multi-sensor obstacle detection system for improvement of rail transport safety

    Ristić-Durrant, Danijela / Haseeb, Muhammad Abdul / Banić, Milan et al. | SAGE Publications | 2022
    Schlagwörter: machine learning

    Single-lever control method design based on power management system and deep reinforcement learning for turboprop engines

    Ji, Run-Min / Huang, Xiang-Hua / Zhang, Xing-Long et al. | SAGE Publications | 2024
    Schlagwörter: deep reinforcement learning

    Self-learning control for coordinated collision avoidance of automated vehicles

    Wang, Yan / Yin, Guodong / Li, Yanjun et al. | SAGE Publications | 2021
    Schlagwörter: self-learning control

    Self-learning approach to automatic transmission shift control in a commercial construction vehicle during the inertia phase

    Hahn, J-O / Hur, J-W / Choi, G-W et al. | SAGE Publications | 2002
    Schlagwörter: self-learning control

    Risk prediction and factor analysis of rider’s injury severity in passenger car and E-bike accidents based on interpretable machine learning

    Wei, Tianzheng / Zhu, Tong / Liu, Haoxue | SAGE Publications | 2024
    Schlagwörter: machine learning

    Research on fault prediction of marine diesel engine based on attention-LSTM

    Liu, Yi / Gan, Huibing / Cong, Yujin et al. | SAGE Publications | 2023
    Schlagwörter: deep learning

    Research on automated parking perception based on a multi-sensor method

    Yang, Yifan / Huang, Jiang / Sun, Kai et al. | SAGE Publications | 2023
    Schlagwörter: deep learning

    Recognition of abnormal car door noise based on multi-scale feature fusion

    Wang, Xiaolan / Song, Yongchao / Su, Lili et al. | SAGE Publications | 2023
    Schlagwörter: transfer learning

    Real-time prediction for the surge of turboshaft engine using multi-branch feature fusion neural network

    Zhang, Xing-Long / Zhang, Tian-Hong / Li, Ling-Wei et al. | SAGE Publications | 2023
    Schlagwörter: deep learning

    Q-learning–based practical disturbance compensation control for hypersonic flight vehicle

    Li, Xu / Zhang, Ziyi / Ji, Yuehui et al. | SAGE Publications | 2023
    Schlagwörter: Q-learning

    Procedure for combining field measurements and machine learning to quantify impact of different track parameters on ride quality of railway tracks

    Roghani, Alireza / Pall, Raman / Toma, Elton | SAGE Publications | 2022
    Schlagwörter: machine learning

    Pressure control based on reinforcement learning strategy of the pneumatic relays for an electric-pneumatic braking system

    Shan, Tianshi / Li, Liang / Wu, Xiuheng et al. | SAGE Publications | 2023
    Schlagwörter: Q-learning

    Prediction of neck injury using multiple linear regression and bumper damage: Case study for low-speed rear-end collisions

    Lee, Jae-Won / Kim, Ji-Hae / Kim, Tae-Won | SAGE Publications | 2022
    Schlagwörter: supervised machine learning