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Statements

Subject Item
n2:RIV%2F61988987%3A17610%2F13%3AA130150A%21RIV13-MSM-17610___
rdf:type
n9:Vysledek skos:Concept
dcterms:description
There is no individual forecasting method that is generally for any given time series better than any other method. There always exists a danger that for a given time series the method is inappropriate. To overcome such a problem, distinct ensemble techniques that combine more forecasting methods are designed. These techniques construct a forecast as a (linear) combination of forecasts by individual methods. This contribution provides a novel ensemble technique that determines the weights based on time series features. The knowledge how to determine weights comes from the regression analysis. In order to capture the desirable issues of robustness and mainly of interpretability, the knowledge how to combine individual methods is encoded in a linguistic description. The mechanism of determination of particular weights is PbLD -- a unique fuzzy inference technique . An experimental justification is provided in order to confirm the promising potential of the given direction of research. There is no individual forecasting method that is generally for any given time series better than any other method. There always exists a danger that for a given time series the method is inappropriate. To overcome such a problem, distinct ensemble techniques that combine more forecasting methods are designed. These techniques construct a forecast as a (linear) combination of forecasts by individual methods. This contribution provides a novel ensemble technique that determines the weights based on time series features. The knowledge how to determine weights comes from the regression analysis. In order to capture the desirable issues of robustness and mainly of interpretability, the knowledge how to combine individual methods is encoded in a linguistic description. The mechanism of determination of particular weights is PbLD -- a unique fuzzy inference technique . An experimental justification is provided in order to confirm the promising potential of the given direction of research.
dcterms:title
On the Potential of Fuzzy Rule-Based Ensemble Forecasting On the Potential of Fuzzy Rule-Based Ensemble Forecasting
skos:prefLabel
On the Potential of Fuzzy Rule-Based Ensemble Forecasting On the Potential of Fuzzy Rule-Based Ensemble Forecasting
skos:notation
RIV/61988987:17610/13:A130150A!RIV13-MSM-17610___
n9:predkladatel
n10:orjk%3A17610
n4:aktivita
n15:S n15:P
n4:aktivity
P(ED1.1.00/02.0070), P(LH12229), S
n4:dodaniDat
n12:2013
n4:domaciTvurceVysledku
n11:3721620 n11:6800327 n11:3252183
n4:druhVysledku
n18:D
n4:duvernostUdaju
n7:S
n4:entitaPredkladatele
n8:predkladatel
n4:idSjednocenehoVysledku
93933
n4:idVysledku
RIV/61988987:17610/13:A130150A
n4:jazykVysledku
n20:eng
n4:klicovaSlova
Time series; ensembles; fuzzy rules
n4:klicoveSlovo
n16:fuzzy%20rules n16:Time%20series n16:ensembles
n4:kontrolniKodProRIV
[A72955FF422E]
n4:mistoKonaniAkce
Ostrava
n4:mistoVydani
Berlín
n4:nazevZdroje
Proc. of 7th International Conference on Soft Computing Models in Industrial and Environmental Applications
n4:obor
n22:BA
n4:pocetDomacichTvurcuVysledku
3
n4:pocetTvurcuVysledku
3
n4:projekt
n13:LH12229 n13:ED1.1.00%2F02.0070
n4:rokUplatneniVysledku
n12:2013
n4:tvurceVysledku
Vavříčková, Lenka Sikora, David Štěpnička, Martin
n4:typAkce
n17:WRD
n4:wos
000312969500050
n4:zahajeniAkce
2012-09-05+02:00
s:issn
2194-5357
s:numberOfPages
10
n19:hasPublisher
Springer-Verlag New York
n21:isbn
978-3-642-33017-9
n5:organizacniJednotka
17610