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Modeling forecast uncertainty using fuzzy clustering

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86096970" target="_blank" >RIV/61989100:27240/13:86096970 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-642-32922-7_30" target="_blank" >http://dx.doi.org/10.1007/978-3-642-32922-7_30</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-642-32922-7_30" target="_blank" >10.1007/978-3-642-32922-7_30</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Modeling forecast uncertainty using fuzzy clustering

  • Original language description

    Numerical Weather Prediction (NWP) systems are state-of-the-art atmospheric models that can provide forecasts of various weather attributes. These forecasts are used in many applications as critical inputs for planning and decision making. However, NWP systems cannot supply any information about the uncertainty of the forecasts as their immediate outputs. In this paper, we investigate the application of Fuzzy C-means clustering as a powerful soft computing technique to discover classes of weather situations that follow similar forecast uncertainty patterns. These patterns are then utilized by distribution fitting methods to obtain Prediction Intervals (PIs) that can express the expected accuracy of the NWP system outputs. Three years of weather forecast records were used in a set of experiments to empirically evaluate the applicability of the proposed approach and the accuracy of the computed PIs. Results confirm that the PIs generated by the proposed post-processing procedure have a h

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    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

    Advances in Intelligent Systems and Computing

  • ISBN

    978-3-642-32921-0

  • ISSN

    2194-5357

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    287-296

  • Publisher name

    Springer

  • Place of publication

    Heidelberg

  • Event location

    Ostrava

  • Event date

    Sep 5, 2012

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article