Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F16%3A70194" target="_blank" >RIV/60460709:41330/16:70194 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1155/2016/3868519" target="_blank" >http://dx.doi.org/10.1155/2016/3868519</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1155/2016/3868519" target="_blank" >10.1155/2016/3868519</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks

Popis výsledku v původním jazyce

The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feed forward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI) and the standardized precipitation evaporation index (SPEI) andwere derived for the period of 1948-2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feed forward multilayer perceptron with one hidden layer of neurons.

Název v anglickém jazyce

Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks

Popis výsledku anglicky

The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feed forward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI) and the standardized precipitation evaporation index (SPEI) andwere derived for the period of 1948-2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feed forward multilayer perceptron with one hidden layer of neurons.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

DA - Hydrologie a limnologie

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název periodika

Computational Intelligence and Neuroscience

ISSN

1687-5265

e-ISSN

—

Svazek periodika

2016

Číslo periodika v rámci svazku

3868519

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

17

Strana od-do

1-17

Kód UT WoS článku

000370270000001

EID výsledku v databázi Scopus

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