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[64520] Artykuł: Time-series-dynamics modeling and forecasting - an accurate and interpretable genetic-fuzzy approachCzasopismo: Advances in Intelligent Systems and Computing Tom: 642, Strony: 165-175ISSN: 2194-5357 Wydawca: SPRINGER INTERNATIONAL PUBLISHING AG, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND Opublikowano: 2017 Miejsce wydania: Cham Autorzy / Redaktorzy / Twórcy Grupa MNiSW: Materiały z konferencji międzynarodowej (zarejestrowane w Web of Science) Punkty MNiSW: 15 Klasyfikacja Web of Science: Proceedings Paper DOI Web of Science Keywords: time-series-dynamics modeling and forecasting  fuzzy rule-based systems  multi-objective evolutionary optimization  accuracy-interpretability trade-off optimization  |
In this paper, we present the application of our fuzzy rule-based modeling technique with genetically optimized accuracy-interpretability trade-off to time-series-dynamics discovery, modeling, and forecasting. The so-called Box-Jenkins' benchmark, i.e., measurement-based time series describing the behavior of an industrial gas furnace is considered. We employ - as a multi-objective evolutionary optimization algorithm - our generalization - characterized by a higher spread and a better balanced distribution of solutions - of the well-known SPEA2 method. Our approach has been compared with several alternative techniques applied to the same time series data.