Forecast of Consumer Behaviour Based on Neural Networks Models Comparison.

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F12%3A00200599" target="_blank" >RIV/62156489:43110/12:00200599 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Forecast of Consumer Behaviour Based on Neural Networks Models Comparison.

Popis výsledku v původním jazyce

The aim of this article is comparison of accuracy level of forecasted values of several artificial neural network models. The comparison is performed on datasets of Czech household consumption values. Several statistical models en resolve this task withmore or fewer restrictions. In previous work where models' input conditions were not so strict and model with missing data was used (the time series didn't contain many values) we have obtained comparably good results with artificial neural networks. Twoviews - practical and theoretical, motivate the purpose of this study. Forecasting models for medium term prognosis of the main trends of Czech household consumption is part of the faculty research design grant MSM 6215648904/03/02 (Sub-task 5.3) whichdefines the practical purpose. Testing of nonlinear autoregressive artificial neural network model compared with feedforward neural network and radial basis function neural network defines the theoretical purpose. The performance metrics

Název v anglickém jazyce

Forecast of Consumer Behaviour Based on Neural Networks Models Comparison.

Popis výsledku anglicky

The aim of this article is comparison of accuracy level of forecasted values of several artificial neural network models. The comparison is performed on datasets of Czech household consumption values. Several statistical models en resolve this task withmore or fewer restrictions. In previous work where models' input conditions were not so strict and model with missing data was used (the time series didn't contain many values) we have obtained comparably good results with artificial neural networks. Twoviews - practical and theoretical, motivate the purpose of this study. Forecasting models for medium term prognosis of the main trends of Czech household consumption is part of the faculty research design grant MSM 6215648904/03/02 (Sub-task 5.3) whichdefines the practical purpose. Testing of nonlinear autoregressive artificial neural network model compared with feedforward neural network and radial basis function neural network defines the theoretical purpose. The performance metrics

Druh

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

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis

ISSN

1211-8516

e-ISSN

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Svazek periodika

2012

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

6

Strana od-do

437-442

Kód UT WoS článku

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EID výsledku v databázi Scopus

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