Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A Comparative Study of Recurrent Neural Network Architectures for Battery Voltage Prediction


    Beteiligte:
    Cho, Gyouho (Autor:in) / ZHU, DI (Autor:in) / Campbell, Jeffrey (Autor:in)

    Kongress:

    SAE Powertrains, Fuels & Lubricants Digital Summit



    Erscheinungsdatum :

    2021-01-01


    Format / Umfang :

    ALL-ALL



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch



    A Comparative Study of Recurrent Neural Network Architectures for Battery Voltage Prediction

    Cho, Gyouho / ZHU, DI / Campbell, Jeffrey | British Library Conference Proceedings | 2021


    A Comparative Study of Recurrent Neural Network Architectures for Battery Voltage Prediction

    ZHU, DI / Cho, Gyouho / Campbell, Jeffrey | SAE Technical Papers | 2021


    Comparative Study between Equivalent Circuit and Recurrent Neural Network Battery Voltage Models

    Emadi, Ali / Vidal, Carlos / Naguib, Mina et al. | SAE Technical Papers | 2021


    Recurrent Neural Network Architectures for Vulnerable Road User Trajectory Prediction

    Xiong, Hui / Flohr, Fabian B. / Wang, Sijia et al. | IEEE | 2019


    Battery Voltage Prediction Using Neural Networks

    Zhu, Di / Campbell, Jeffrey Joseph / Cho, Gyouho | IEEE | 2021