Open Access
| Issue |
E3S Web Conf.
Volume 108, 2019
Energy and Fuels 2018
|
|
|---|---|---|
| Article Number | 01002 | |
| Number of page(s) | 9 | |
| Section | Energy | |
| DOI | https://doi.org/10.1051/e3sconf/201910801002 | |
| Published online | 05 July 2019 | |
- ARE SA: Statystyka elektroenergetyki polskiej, Warszawa (2004-2016) [Google Scholar]
- I. Pavlova-Marciniak, Implementation of climate policy assumptions in Poland, Proceedings of The 8th International Scientific Symposium ELEKTROENERGETIKA 2015, Stara Lesna, Slovak Republic (2015) [Google Scholar]
- M. Kornatka, A. Gawlak, Comparative analysis of operating conditions in Polish medium-voltage and 110 kV networks, Proceedings of The 8th International Scientific Symposium ELEKTROENERGETIKA 2015, Stara Lesna, Slovak Republic (2015) [Google Scholar]
- M. Kornatka, The weighted kernel density estimation methods for analysing reliability of electricity supply, in: 17th International Scientific Conference on Electric Power Engineering (EPE), Prague (2016) [Google Scholar]
- GUS (Central Statistical Office of Poland), Energy statistics, Gospodarka PaliwowoEnergetyczna. Warszawa (2004 – 2016) [Google Scholar]
- I. Dobrzańska, K. Dąsal, J. Łyp, T. Popławski, J. Sowiński J, Prognozowanie w elektroenergetyce. Zagadnienia wybrane. WPCz Częstochowa (2002) [Google Scholar]
- T. Popławski (ed), K. Dąsal, J. Łyp, J. Sowiński, Wybrane zagadnienia prognozowania długoterminowego w systemach elektroenergetycznych, WPCz Częstochowa (2011) [Google Scholar]
- J.-S.R Jang, ANFIS: Adaptive-Network-Based Fuzzy Inference System, IEEE Trans. Systems, Man, and Cybernetics, 23, 665 (1993) [CrossRef] [Google Scholar]
- D. Rutkowska, M. Piliński, L. Rutkowski, Sieci neuronowe, algorytmy genetyczne i systemy rozmyte, PWN Warszawa (1999) [Google Scholar]
- J. Sowiński, M. Szydłowski, Forecast of Electricity Supply Using Adaptive NeuroFuzzy Inference System, in: Rusek S., Gono R., 18th International Scientific Conference on Electric Power Engineering, IEEE New York (2017) [Google Scholar]
- J. Sowiński, Medium-Term Forecast of Monthly Supply of Electricity and MaximumDemand-Day Power Using Adaptive Neuro-Fuzzy Inference System, in: M. Kolcun, I. Kolcunova, J. Kurimsky, 9th International Scientific Symposium on Electrical Power Engineering, Stara Leśna, Słowacja (2017) [Google Scholar]
- L.-Ch. Ying, M.-Ch. Pan, Using adaptive network based fuzzy inference system to forecast regional electricity loads, Energy Conversion and Management, 49, 205 (2008) [Google Scholar]
- L.A. Zadeh, Fuzzy sets. Information and Control, 8, 338 (1965) [CrossRef] [Google Scholar]
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