Forecasting Direction of Trend of a Group of Analogous Time Series Using F-Transform and Fuzzy Natural Logic

Forecasting Direction of Trend of a Group of Analogous Time Series Using F-Transform and Fuzzy Natural Logic

We present an idea to group time series according to similarity of their local trends and to predict future direction of the trend of all of them on the basis of forecast of only one representative. First, we assign to each time series an adjoint one, which consists of a sequence of the F1-transform...

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Bibliographic Details
Main Authors: Vilém Novák, Irina Perfilieva
Format: Article
Language:English
Published: Atlantis Press 2015-12-01
Series:International Journal of Computational Intelligence Systems
Subjects:
F-transform
time series
Fuzzy Natural Logic
evaluative linguistic expressions
Online Access:https://www.atlantis-press.com/article/25868661.pdf
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spelling doaj-593679d91d574c37aff21902f7567f072020-11-25T01:42:38ZengAtlantis PressInternational Journal of Computational Intelligence Systems 1875-68832015-12-01810010.1080/18756891.2015.1129575Forecasting Direction of Trend of a Group of Analogous Time Series Using F-Transform and Fuzzy Natural LogicVilém NovákIrina PerfilievaWe present an idea to group time series according to similarity of their local trends and to predict future direction of the trend of all of them on the basis of forecast of only one representative. First, we assign to each time series an adjoint one, which consists of a sequence of the F1-transform components. Then, they are grouped together according to their similarity, a principal time series is selected in each group and its future course is forecasted. Finally, directions of trends of the other time series from the same group are computed using special methods of fuzzy natural logic.https://www.atlantis-press.com/article/25868661.pdfF-transformtime seriesFuzzy Natural Logicevaluative linguistic expressions
collection DOAJ
language English
format Article
sources DOAJ
author Vilém Novák
Irina Perfilieva
spellingShingle Vilém Novák
Irina Perfilieva
Forecasting Direction of Trend of a Group of Analogous Time Series Using F-Transform and Fuzzy Natural Logic
International Journal of Computational Intelligence Systems
F-transform
time series
Fuzzy Natural Logic
evaluative linguistic expressions
author_facet Vilém Novák
Irina Perfilieva
author_sort Vilém Novák
title Forecasting Direction of Trend of a Group of Analogous Time Series Using F-Transform and Fuzzy Natural Logic
title_short Forecasting Direction of Trend of a Group of Analogous Time Series Using F-Transform and Fuzzy Natural Logic
title_full Forecasting Direction of Trend of a Group of Analogous Time Series Using F-Transform and Fuzzy Natural Logic
title_fullStr Forecasting Direction of Trend of a Group of Analogous Time Series Using F-Transform and Fuzzy Natural Logic
title_full_unstemmed Forecasting Direction of Trend of a Group of Analogous Time Series Using F-Transform and Fuzzy Natural Logic
title_sort forecasting direction of trend of a group of analogous time series using f-transform and fuzzy natural logic
publisher Atlantis Press
series International Journal of Computational Intelligence Systems
issn 1875-6883
publishDate 2015-12-01
description We present an idea to group time series according to similarity of their local trends and to predict future direction of the trend of all of them on the basis of forecast of only one representative. First, we assign to each time series an adjoint one, which consists of a sequence of the F1-transform components. Then, they are grouped together according to their similarity, a principal time series is selected in each group and its future course is forecasted. Finally, directions of trends of the other time series from the same group are computed using special methods of fuzzy natural logic.
topic F-transform
time series
Fuzzy Natural Logic
evaluative linguistic expressions
url https://www.atlantis-press.com/article/25868661.pdf
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AT irinaperfilieva forecastingdirectionoftrendofagroupofanalogoustimeseriesusingftransformandfuzzynaturallogic
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