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Rainfall-runoff time series modeling with artificial neural network usage

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13520%2F10%3A00006084" target="_blank" >RIV/44555601:13520/10:00006084 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Rainfall-runoff time series modeling with artificial neural network usage

  • Original language description

    The most required forecast is a six hours ahead estimation of runoff volume. The source data consist of several hourly data time series, like runoff, rainfall and API. We compared linear regression, last value estimation, multilayer perceptron and evolved multilayer perceptron.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    DA - Hydrology and limnology

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2010

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Hydrological responses of small basins to a changing environment

  • ISBN

    978-3-900962-90-6

  • ISSN

  • e-ISSN

  • Number of pages

    3

  • Pages from-to

  • Publisher name

    BOKU Vídeň

  • Place of publication

    Rakousko

  • Event location

    Seggau, Rakousko

  • Event date

    Jan 1, 2010

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article