With the more and more serious problems such as urban traffic accident and jam etc, how to finish short-term traffic forecast is becoming the premise and key of achieving traffic control and inducement. A new forecast method for city short-term traffic flows is presented, based on neuro-fuzzy decision tree method which is different from traditional models and improves FDT's classification accuracy and extracts more accuracy human interpretable classification rules. The results indicate that this method is valid for short-term traffic flows prediction and it will have a good application prospect in this area.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Urban Short-Term Traffic Flow Prediction Based on Neuro-FDT


    Beteiligte:
    Jin, Hongxia (Autor:in)

    Kongress:

    First International Conference on Transportation Engineering ; 2007 ; Southwest Jiaotong University, Chengdu, China



    Erscheinungsdatum :

    2007-07-09




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Urban Short-Term Traffic Flow Prediction Based on Neuro-FDT

    Jin, H. / China Communications and Transportation Association; Transportation & Development Institute (American Society of Civil Engineers) | British Library Conference Proceedings | 2007


    Short term traffic flow prediction based on neuro-fuzzy hybrid sytem

    Deshpande, Minal / Bajaj, Preeti R. | IEEE | 2016


    Urban Short-Term Traffic Flow Prediction Based on Stacked Autoencoder

    Zhao, Xinran / Gu, Yuanli / Chen, Lun et al. | ASCE | 2019


    The Urban Road Short-Term Traffic Flow Prediction Research

    Qin, Zhen Hai | Trans Tech Publications | 2013


    Urban short-term traffic flow prediction method, system and equipment

    XU XING / HU XIANQI / ZHAO YUN | Europäisches Patentamt | 2024

    Freier Zugriff