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Towards Robust and Accurate Traffic Prediction Using Parallel Multiobjective Genetic Algorithms and Support Vector Regression

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F15%3APU117000" target="_blank" >RIV/00216305:26230/15:PU117000 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.fit.vut.cz/research/publication/10886/" target="_blank" >https://www.fit.vut.cz/research/publication/10886/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ITSC.2015.360" target="_blank" >10.1109/ITSC.2015.360</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Towards Robust and Accurate Traffic Prediction Using Parallel Multiobjective Genetic Algorithms and Support Vector Regression

  • Original language description

    The support vector regression (SVR) is a very successful method in solving many difficult tasks in the area of traffic prediction. However, the performance of SVR is very sensitive to the parameters setting and the selection of input variables such as sensors providing the input data. In this paper, we describe a new method, which simultaneously optimizes the meta-parameters of SVR model and the subset of its input variables. The method is based on a multiobjective genetic algorithm. The proposed implementation is intended for a parallel environment supporting OpenMP. We evaluated the method in the tasks of data imputation, short term prediction of traffic variables and travel times prediction using real world open data. It was confirmed that the simultaneous optimization of SVR parameters and input variables provides better quality of prediction than previous methods.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2015 IEEE 18th International Conference on Intelligent Transportation Systems

  • ISBN

    978-1-4673-6596-3

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    2231-2236

  • Publisher name

    IEEE Computer Society

  • Place of publication

    Los Alamitos

  • Event location

    Las Palmas de Gran Canaria

  • Event date

    May 1, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000376668802050