A relatively new method for data analysis called the adaptive neuro-fuzzy inference system (ANFIS) is illustrated with an example from travel behavior modeling. The options offered by this data analysis technique are illustrated by using data from Australia. In addition, an experiment was performed to identify the optimal split of data into an estimation sample and a validation sample. Comparisons of ANFIS and the more traditional regression methods such as ordinary least-squares linear regression and negative binomial regression were performed by using the mean square error and correlation coefficients. ANFIS is shown to be a useful tool, and its further use in travel behavior research and applications in transportation planning is recommended. However, many additional issues require further scrutiny and experimentation, which are discussed.


    Zugriff

    Download

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Application of Adaptive Neuro-Fuzzy Inference System to Analysis of Travel Behavior


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:


    Erscheinungsdatum :

    01.01.2003




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Application of Adaptive Neuro-fuzzy Inference System for road accident prediction

    Hosseinpour, Mehdi / Yahaya, Ahmad Shukri / Ghadiri, Seyed Mohammadreza et al. | Online Contents | 2013


    Application of Adaptive Neuro-fuzzy Inference System for road accident prediction

    Hosseinpour, Mehdi / Yahaya, Ahmad Shukri / Ghadiri, Seyed Mohammadreza et al. | Springer Verlag | 2013


    Vehicle Classification Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

    Maurya, Akhilesh Kumar / Patel, Devesh Kumar | Springer Verlag | 2014


    Dynamic modelling of PEMFC by adaptive neuro-fuzzy inference system

    Karimi, Milad / Rezazadeh, Alireza | British Library Online Contents | 2016