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Uncertainty modelling in Rainfall-Runoff simulations based on parallel Monte Carlo method

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86094058" target="_blank" >RIV/61989100:27240/15:86094058 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27740/15:86094058

  • Result on the web

    <a href="http://dx.doi.org/10.14311/NNW.2015.25.014" target="_blank" >http://dx.doi.org/10.14311/NNW.2015.25.014</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.14311/NNW.2015.25.014" target="_blank" >10.14311/NNW.2015.25.014</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Uncertainty modelling in Rainfall-Runoff simulations based on parallel Monte Carlo method

  • Original language description

    This article describes statistical evaluation of the computational model for precipitation forecast and proposes a method for uncertainty modelling of rainfall-runoff models in the Floreon+ system based on this evaluation. The Monte-Carlo simulation method is used for estimating possible river discharge and provides several confidence intervals that can support the decisions in operational disaster management. Experiments with other parameters of the model and their influence on final river discharge are also discussed.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    IN - Informatics

  • 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

    2015

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Neural Network World

  • ISSN

    1210-0552

  • e-ISSN

  • Volume of the periodical

    Vol. 25(3)

  • Issue of the periodical within the volume

    Vol. 25(3)

  • Country of publishing house

    CZ - CZECH REPUBLIC

  • Number of pages

    10

  • Pages from-to

    267-286

  • UT code for WoS article

    000358101800003

  • EID of the result in the Scopus database