This work presents an intelligent neuron model, which is based on linearly independent functions and sigmoid function with adjustable parameters. It is proved that the information storage ability of this intelligent neuron is greatly improved compared with traditional ones, consequently greatly improves the information processing ability of the whole neural network. Meanwhile, this paper forms a generalized neural network model by these intelligent neurons, and uses this generalized neural network to predict traffic flow data of DaLian city. Experiment shows that the results predicted by this generalized neural network are greatly superior to the ones predicted by traditional back-propagation neural network, and meet the practical requirements well.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Traffic flow prediction based on generalized neural network


    Beteiligte:
    Guozhen Tan, (Autor:in) / Wenjiang Yuan, (Autor:in) / Hao Ding, (Autor:in)


    Erscheinungsdatum :

    2004-01-01


    Format / Umfang :

    297448 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Traffic flow prediction method based on adaptive generalized PageRank graph neural network

    LU WEI / KONG XIANGYUAN / XING WEIWEI et al. | Europäisches Patentamt | 2023

    Freier Zugriff

    Traffic flow prediction using neural network

    Jiber, Mouna / Lamouik, Imad / Ali, Yahyaouy et al. | IEEE | 2018


    Traffic flow prediction method based on neural network

    GUO TANGYI / DENG HONG / YANG YONG et al. | Europäisches Patentamt | 2020

    Freier Zugriff


    Traffic flow prediction method based on Fourier-recursive neural network

    WANG CUN / DONG XIAOFEI | Europäisches Patentamt | 2020

    Freier Zugriff