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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

    Visual recognition of hexagonal headed bolts by comparing ICA to wavelets

    Mazzeo, P.L. / Ancona, N. / Stella, E. et al. | Tema Archiv | 2003
    Schlagwörter: maschinelles Sehen , Lernen

    Vibration-based Damage Detection in Bridges via Machine Learning

    Sun, Shuang / Liang, Li / Li, Ming et al. | Springer Verlag | 2018
    Schlagwörter: machine learning

      Vibration-based Damage Detection in Bridges via Machine Learning

      Sun, Shuang / Liang, Li / Li, Ming et al. | Online Contents | 2018
      Schlagwörter: machine learning

    Verification of Image-Based Neural Network Controllers Using Generative Models

    Katz, Sydney M. / Corso, Anthony L. / Strong, Christopher A. et al. | AIAA | 2022
    Schlagwörter: Machine Learning

    Vehicular fuel consumption estimation using real-world measures through cascaded machine learning modeling

    Moradi, Ehsan / Miranda-Moreno, Luis | Elsevier | 2020
    Schlagwörter: Machine learning

    UUV teams, control from a biological perspective

    McDowell, P. / Chen, J. / Bourgeois, B. | Tema Archiv | 2002
    Schlagwörter: Lernen , maschinelles Lernen

    Using supervised machine learning algorithms in pavement degradation monitoring

    Freier Zugriff
    Amir Shtayat / Sara Moridpour / Berthold Best et al. | DOAJ | 2023
    Schlagwörter: Machine Learning

    Using explainable machine learning to understand how urban form shapes sustainable mobility

    Wagner, Felix / Milojevic-Dupont, Nikola / Franken, Lukas et al. | Elsevier | 2022
    Schlagwörter: Explainable machine learning

    Using Deep Learning to Predict Unstable Approaches for General Aviation Aircraft

    Jain, Tanish / Misra, Shlok / Truong, Dothang | AIAA | 2022
    Schlagwörter: Machine Learning

    Urban traffic control based on learning agents

    Gregoire, P.L. / Desjardins, C. / Laumonier, J. et al. | Tema Archiv | 2007
    Schlagwörter: Lernen , maschinelles Lernen

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