Kvantitatívní nástroje a soft computing v manažerských informačních systémech

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F06%3A%230000170" target="_blank" >RIV/47813059:19240/06:#0000170 - 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

Quantitative tools and soft computing in management information systems

Popis výsledku v původním jazyce

The general methodological framework of classical econometric approach and soft computing approach are considered to forecast economic time series. Some theoretical concepts are discussed. The article introduces the concept of econometric and time seriesmodelling, demonstrates some of the classical and later econometric models, discusses the use of decomposition techniques to model and forecast time series described by trend and seasonal components. The use of co-integration concept is discussed as well. The autoregressive and direct smoothing procedures and transfer function models and several applications illustrating these approaches in practical situations are introduced and presented. Finally, we introduce and examine the use of novel-modelling techniques such as learning from experimental data (statistical learning) neural networks and fuzzy logic methods.

Název v anglickém jazyce

Quantitative tools and soft computing in management information systems

Popis výsledku anglicky

The general methodological framework of classical econometric approach and soft computing approach are considered to forecast economic time series. Some theoretical concepts are discussed. The article introduces the concept of econometric and time seriesmodelling, demonstrates some of the classical and later econometric models, discusses the use of decomposition techniques to model and forecast time series described by trend and seasonal components. The use of co-integration concept is discussed as well. The autoregressive and direct smoothing procedures and transfer function models and several applications illustrating these approaches in practical situations are introduced and presented. Finally, we introduce and examine the use of novel-modelling techniques such as learning from experimental data (statistical learning) neural networks and fuzzy logic methods.

Druh

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

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

<a href="/cs/project/GA402%2F05%2F2768" target="_blank" >GA402/05/2768: Pokročilé statistické a ekonometrické techniky pro modelování a predikci ekonomických časových řad</a><br>

Návaznosti

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

Rok uplatnění

2006

Kód důvěrnosti údajů

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

Název periodika

Jounal of Information, Control and Management Sytems

ISSN

1336-1716

e-ISSN

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Svazek periodika

4

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

SK - Slovenská republika

Počet stran výsledku

12

Strana od-do

23-34

Kód UT WoS článku

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EID výsledku v databázi Scopus

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