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Description
  • Based on work by Song and Chisson Fuzy time series and its models a fuzzy time series model is proposed and applied to predict chaotic financial time series. To determine the fuzzy relations from the data a neural network was proposed which by product-space clustering technique adaptively generate the fuzzy rules. As an application of proposed method, the estimate of the inflation is carried out.
  • Based on work by Song and Chisson Fuzy time series and its models a fuzzy time series model is proposed and applied to predict chaotic financial time series. To determine the fuzzy relations from the data a neural network was proposed which by product-space clustering technique adaptively generate the fuzzy rules. As an application of proposed method, the estimate of the inflation is carried out. (en)
  • Na základě práce podle Songa a Chissona (Fuzy time series and its models) je navržen model fuzzy časové řady pro predikci chaoitických finančních procesů. Pomocí neuronové sítě s implementaci vyhledávání klustrů ve vstupně-výstupních datech se adaptivním postupem postupně generují fuzzy pravidla (relace). Postup byl aplikován na modelování a predikci reálního procesu vývoje inflace. (cs)
Title
  • Modelling of Fuzzy Time Series with Application to Inflation Data
  • Modelování fuzzy časových řad s aplikací na data inflace (cs)
  • Modelling of Fuzzy Time Series with Application to Inflation Data (en)
skos:prefLabel
  • Modelling of Fuzzy Time Series with Application to Inflation Data
  • Modelování fuzzy časových řad s aplikací na data inflace (cs)
  • Modelling of Fuzzy Time Series with Application to Inflation Data (en)
skos:notation
  • RIV/47813059:19240/06:#0000167!RIV07-GA0-19240___
http://linked.open.../vavai/riv/strany
  • 95-100
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  • P(GA402/05/2768)
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  • 486229
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  • RIV/47813059:19240/06:#0000167
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  • product-space clustering; econometric modelling; supervised competitive learnig (en)
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  • [ADC37EE302BB]
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  • Marček, Dušan
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number of pages
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  • Evropský polytechnický istitut, s.r.o.
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  • 80-7314-083-7
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  • 19240
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