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Possibilities of using neural networks for data preprocessing in models predicting flash floods

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020699%3A_____%2F21%3AN0000160" target="_blank" >RIV/00020699:_____/21:N0000160 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.chmi.cz/files/portal/docs/reditel/SIS/nakladatelstvi/assets/dunajska-konference.pdf" target="_blank" >https://www.chmi.cz/files/portal/docs/reditel/SIS/nakladatelstvi/assets/dunajska-konference.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Possibilities of using neural networks for data preprocessing in models predicting flash floods

  • Original language description

    In the article are studied possibilities of preprocessing of the radar values using methods artificial intelligence (neural network). For this study were chosen 229 meteorological stations. The data from these stations are compared with mean values of radar data. The neural networks are trained on historical episodes (2016-2019) and whole model is tested on validation period, which it was chosen year 2020. The preprocessed data and were given to model for forecasting of flash flood danger and results of both inputs were compared. Preprocessed rainfall data significantly lowered number of fake alarms, but slightly increased number of missed dangerous events. Results of neural networks model were good enough for another continuation of this applications. Where should be find some problematic issues with the neural network application as preprocessing tool for this application.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10501 - Hydrology

Result continuities

  • Project

    <a href="/en/project/VI20192021166" target="_blank" >VI20192021166: Hydrometeorological risks in the Czech Republic - changes and prediction enhancements</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    XXIX Danube Conference - XXIX Conference of the Danubian Countries on Hydrological Forecasting and Hydrological Bases of Water Management

  • ISBN

    978-80-7653-031-7

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    123-126

  • Publisher name

    Czech Hydrometeorological Institute

  • Place of publication

    Praha

  • Event location

    Brno

  • Event date

    Sep 6, 2021

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article