Objective Functions in Fuzzy Cognitive Maps: the Case of Time Series Modeling

Władysław Homenda , Agnieszka Jastrzębska


Modeling time series is a well investigated area for a long period. During last years fuzzy cognitive maps have been successfully employed for this purpose. Easy interpretation of relations and dependencies in an information space raised by time series is an important aspect of latest researches, which brought time series processing from an elementary, numerical, level to a space of concepts created by a given time series. In this paper we investigate time series modeling with fuzzy cognitive maps at a concept level. Discussion is focused on constructions of fuzzy cognitive maps for a given time series which is transformed to a level of concepts. Attention is payed on objective functions, which are employed to training and quality evaluating of fuzzy cognitive maps. Several types of objective functions are proposed, discussed and tested. Objective functions studied in this paper are based on mean square error and maximal square error.
Author Władysław Homenda (FMIS / DSMKP) - Faculty of Economics and Informatics in Vilnius, University of Bialystok, Kalvariju G. 135, LT-08221 Vilnius, Lithuania (UwB)
Władysław Homenda,,
- Department of Structural Methods for Knowledge Processing
, Agnieszka Jastrzębska (FMIS / DSMKP)
Agnieszka Jastrzębska,,
- Department of Structural Methods for Knowledge Processing
Publication size in sheets0.5
Book Proceedings of 2018 Joint 7th International Conference on Informatics, Electronics & Vision (ICIEV) and 2018 2nd International Conference on Imaging, Vision & Pattern Recognition (icIVPR), 2018, IEEE, ISBN 978-1-5386-5164-3
Keywords in Polishszereg czasowy, rozmyta mapa poznawcza, błędy modelu, optymalizacja
Keywords in Englishtime series, fuzzy cognititve maps, model error, optimization
Abstract in PolishW pracy przedstawione zostało studium nad zagadnieniem optymalizacji rozmytych map poznawczych. Konkretna kategoria problemów, które były rozwiązywane to prognoza szeregów czasowych. Zbadane zostały różne kryteria optymalizacji, które można użyć w celu optymalizacji macierzy wag. Wskazano różnice jakościowe pomiędzy wybranym kryterium optymalizacji a właściwościami macierzy wag. Wyniki przedstawione w pracy mogą posłużyć innym do wyboru właściwego kryterium przy konstrukcji modelu mapy poznawczej.
URL http://toc.proceedings.com/42406webtoc.pdf
Languageen angielski
Score (nominal)0
Score sourceconferenceList
ScoreMinisterial score = 0.0, 20-10-2019, ChapterFromConference
Publication indicators WoS Citations = 0; Scopus Citations = 0
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