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Verification of Bayesian Clustering in Travel Behaviour Research – First Step to Macroanalysis of Travel Behaviour

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F18%3A00327455" target="_blank" >RIV/68407700:21260/18:00327455 - isvavai.cz</a>

  • Result on the web

    <a href="http://iopscience.iop.org/article/10.1088/1755-1315/140/1/012067/pdf" target="_blank" >http://iopscience.iop.org/article/10.1088/1755-1315/140/1/012067/pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1088/1755-1315/140/1/012067" target="_blank" >10.1088/1755-1315/140/1/012067</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Verification of Bayesian Clustering in Travel Behaviour Research – First Step to Macroanalysis of Travel Behaviour

  • Original language description

    Our research is looking at the travel behaviour from a macroscopic view, taking one municipality as a basic unit. The travel behaviour of one municipality as a whole is becoming one piece of a data in the research of travel behaviour of a larger area, perhaps a country. A data pre-processing is used to cluster the municipalities in groups, which show similarities in their travel behaviour. Such groups can be then researched for reasons of their prevailing pattern of travel behaviour without any distortion caused by municipalities with a different pattern. This paper deals with actual settings of the clustering process, which is based on Bayesian statistics, particularly the mixture model. An optimization of the settings parameters based on correlation of pointer model parameters and relative number of data in clusters is helpful, however not fully reliable method. Thus, method for graphic representation of clusters needs to be developed in order to check their quality. A training of the setting parameters in 2D has proven to be a beneficial method, because it allows visual control of the produced clusters. The clustering better be applied on separate groups of municipalities, where competition of only identical transport modes can be found.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20104 - Transport engineering

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    IOP Conference Series: Earth and Environmental Science

  • ISBN

  • ISSN

    1755-1307

  • e-ISSN

    1755-1315

  • Number of pages

    9

  • Pages from-to

  • Publisher name

    IOP Publishing Ltd.

  • Place of publication

    Bristol

  • Event location

    Langkawi

  • Event date

    Dec 4, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000454977100067