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[83010] Artykuł: Application of Fuzzy Cognitive Maps to Multi-step Ahead Prediction of Electricity ConsumptionCzasopismo: 2018 Conference on Electrotechnology: Processes, Models, Control and Computer Science (EPMCCS) Tom: 1, Strony: 1-5ISBN: 978-1-5386-8255-5 Wydawca: IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA Opublikowano: 2018 Autorzy / Redaktorzy / Twórcy Grupa MNiSW: Materiały z konferencji międzynarodowej (zarejestrowane w Web of Science) Punkty MNiSW: 15 Klasyfikacja Web of Science: Proceedings Paper ![]() ![]() ![]() Keywords: fuzzy cognitive maps  multi-step ahead time series prediction  electricity consumption   |
This paper is devoted to the multi-step ahead prediction of multivariate time series with the use of fuzzy cognitive maps. The aim of the analysis is to predict the electricity consumption in a household. The learning process was performed with the developed Structure Optimization Genetic Algorithm (SOGA). A comparison with the well-known method for fuzzy cognitive maps learning: the Real-Coded Genetic Algorithm was done. The obtained results show that the SOGA algorithm enables simplifying the fuzzy cognitive map by selection of the most significant concepts and connections and forecasting the three next steps of electricity consumption with satisfactory accuracy.