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

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020699%3A_____%2F21%3AN0000045" target="_blank" >RIV/00020699:_____/21:N0000045 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

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
—

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)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
XXIX Danube Conference - XXIX Conference of the Danubian Countries on Hydrological Forecasting and Hydrological Bases of Water Management - Conference proceedings - Extended abstracts
ISBN
978-80-7653-017-1
ISSN
—
e-ISSN
—
Number of pages
2
Pages from-to
73-74
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
—

Similar results(10)