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On the Potential of Fuzzy Rule-Based Ensemble Forecasting

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F13%3AA130150A" target="_blank" >RIV/61988987:17610/13:A130150A - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    On the Potential of Fuzzy Rule-Based Ensemble Forecasting

  • Original language description

    There is no individual forecasting method that is generally for any given time series better than any other method. There always exists a danger that for a given time series the method is inappropriate. To overcome such a problem, distinct ensemble techniques that combine more forecasting methods are designed. These techniques construct a forecast as a (linear) combination of forecasts by individual methods. This contribution provides a novel ensemble technique that determines the weights based on timeseries features. The knowledge how to determine weights comes from the regression analysis. In order to capture the desirable issues of robustness and mainly of interpretability, the knowledge how to combine individual methods is encoded in a linguisticdescription. The mechanism of determination of particular weights is PbLD -- a unique fuzzy inference technique . An experimental justification is provided in order to confirm the promising potential of the given direction of research.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BA - General mathematics

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

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

Others

  • Publication year

    2013

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proc. of 7th International Conference on Soft Computing Models in Industrial and Environmental Applications

  • ISBN

    978-3-642-33017-9

  • ISSN

    2194-5357

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    487-496

  • Publisher name

    Springer-Verlag New York

  • Place of publication

    Berlín

  • Event location

    Ostrava

  • Event date

    Sep 5, 2012

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000312969500050