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Description
  • This paper continues development of the innovative method of time series analysis and forecasting using special soft-computing techniques: fuzzy transform and FLb-logic models of natural language semantics. Wewill demonstrate that the F-transform is a powerful technique for extraction of the trend-cycle of timeseries.
  • This paper continues development of the innovative method of time series analysis and forecasting using special soft-computing techniques: fuzzy transform and FLb-logic models of natural language semantics. Wewill demonstrate that the F-transform is a powerful technique for extraction of the trend-cycle of timeseries. (en)
Title
  • Time Series Trend Extraction and its Linguistic Evaluation Using F-Transform and Fuzzy Natural Logic
  • Time Series Trend Extraction and its Linguistic Evaluation Using F-Transform and Fuzzy Natural Logic (en)
skos:prefLabel
  • Time Series Trend Extraction and its Linguistic Evaluation Using F-Transform and Fuzzy Natural Logic
  • Time Series Trend Extraction and its Linguistic Evaluation Using F-Transform and Fuzzy Natural Logic (en)
skos:notation
  • RIV/61988987:17610/12:A130163S!RIV13-MSM-17610___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
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  • P(ED1.1.00/02.0070), P(LH12229)
http://linked.open...vai/riv/dodaniDat
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  • 174466
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  • RIV/61988987:17610/12:A130163S
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  • Time series; fuzzy logic; fuzzy transform (en)
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  • [F1B8ABFE66C6]
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  • Baku
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  • Baku
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  • Proc. 2nd World Conference on Soft Computing
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  • Pavliska, Viktor
  • Štěpnička, Martin
  • Novák, Vilém
  • Štěpničková, Lenka
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http://linked.open.../riv/zahajeniAkce
number of pages
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  • MINISTRY OF COMMUNICATIONS AND INFORMATION TECHNOLOGIES OF THE REPUBLIC OF AZERBAIJAN
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  • 978-9952-452-37-2
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  • 17610
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