Fuzzy Rule-Based Ensemble Forecasting: Introductory Study

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Fuzzy Rule-Based Ensemble Forecasting: Introductory Study

Popis výsledku v původním jazyce

There is no individual forecasting method that is generally for any given time series better than any other method. Thus, no matter the efficiency of a chosen method, there always exists a danger that for a given time series the chosen method is inappropriate. To overcome such a problem and avoid the above mentioned danger, distinct ensemble techniques that combine more individual forecasting methods are designed. These techniques basically construct a forecast as a linear combination of forecasts by individual methods. In this contribution, we construct a novel ensemble technique that determines the weights based on time series features. The protocol that carries a knowledge how to combine the individual forecasts is a fuzzy rule base (linguistic description). An exhaustive experimental justification is provided. The suggested ensemble approach based on fuzzy rules demonstrates both, lower forecasting error and higher robustness.

Název v anglickém jazyce

Fuzzy Rule-Based Ensemble Forecasting: Introductory Study

Popis výsledku anglicky

There is no individual forecasting method that is generally for any given time series better than any other method. Thus, no matter the efficiency of a chosen method, there always exists a danger that for a given time series the chosen method is inappropriate. To overcome such a problem and avoid the above mentioned danger, distinct ensemble techniques that combine more individual forecasting methods are designed. These techniques basically construct a forecast as a linear combination of forecasts by individual methods. In this contribution, we construct a novel ensemble technique that determines the weights based on time series features. The protocol that carries a knowledge how to combine the individual forecasts is a fuzzy rule base (linguistic description). An exhaustive experimental justification is provided. The suggested ensemble approach based on fuzzy rules demonstrates both, lower forecasting error and higher robustness.

Druh

D - Stať ve sborníku

CEP obor

BA - Obecná matematika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

Synergies of Soft Computing and Statistics for Intelligent Data Analysis (Advances in Intelligent Systems and Computing))

ISBN

978-3-642-33041-4

ISSN

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e-ISSN

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Počet stran výsledku

9

Strana od-do

379-387

Název nakladatele

Springer

Místo vydání

Heidelberg

Místo konání akce

Konstanz

Datum konání akce

1. 1. 2012

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000312969600041