Accesso libero

Neural modeling of prices on the Day-Ahead Market at the Polish Power Exchange supported by an evolutionary algorithm and inspired by quantum computing

INFORMAZIONI SU QUESTO ARTICOLO

Cita

Adamowski, J. (2019) Podstawy obliczeń kwantowych [Foundations of quantum calculations; in Polish]. Lectures at the Faculty of Physics and Applied Informatics, AGH University, Kraków, http://www.ftj.agh.edu.pl (access: 14.08.2019) Search in Google Scholar

Alaminos, D., Esteban, I. et al. (2020) Quantum Neural Networks for Forecasting Inflation Dynamics. Journal of Scientific & Industrial Research, 79, 2, doi: 10.56042/jsir.v79i2.68439 (access: 12.12.2022) Search in Google Scholar

Bai, J. and Ng, S. (2002) Determining the Number of Factors in Approximate Factor Models. Econometrica, 70, 1, 191–221. Search in Google Scholar

Bernhardt, C. (2020) Obliczenia kwantowe dla każdego [Quantum calculus for everyone; in Polish]. PWN, Warszawa. Search in Google Scholar

Bissing, D., Klein, M. T. et al. (2019) A Hybrid Regression Model for Day-Ahead Energy Price Forecasting. IEEE Access, 7, 36833-36842. Search in Google Scholar

Catalão, J., Mariano S. et al. (2022) An Artificial Neural Network Approach for Day-Ahead Electricity Prices Forecasting. Proceedings of the 6th WSEAS Int. Conf. on Neural Networks, Lisbon, Portugal, June 16-18, 2022; 80-83. Search in Google Scholar

Chudy, M. (2011) Wprowadzenie do informatyki kwantowej [Introduction into Quantum Informatics; in Polish]. OW EXIT, Warszawa. Search in Google Scholar

Ciechulski, T. and Osowski S. (2014) Badanie jakości predykcji obciążeń elektroenergetycznych za pomocą sieci neuronowych SVM, RBF i MLP [Analysing the quality of prediction of electric energy load with neural networks SVM, RBF and MLP; in Polish]. Przegląd Elektrotechniczny, 90, 8, 148-151. Search in Google Scholar

Conejo, A. J., Plazas M. A. et al. (2005) Day-ahead electricity price forecasting using the wavelet transform and ARIMA models. IEEE Transactions on Power Systems, 20, 2, 1035-1042. Search in Google Scholar

Feynman, R. P., Leughton, R. B. and Sands M. (2014) Feynmana wyk lady z fizyki [Feynman’s lectures in physics; in Polish]. Volume 3. Mechanika kwantowa [Quantum mechanics]. PWN, Warszawa. Search in Google Scholar

Ge, L. and Wenping, M. (2022) A quantum artificial neural network for stock closing price prediction. Information Sciences, 598, 75-85, doi.org/10.1016/j.ins.2022.03.064 (access: 10.12.2022) Search in Google Scholar

Heller, M. (2016) Elementy mechaniki kwantowej dla filozofów [Elements of quantum mechanics for philosophers; in Polish]. Copernicus Center Press, Kraków. Search in Google Scholar

Hirvensalo, M. (2004) Algorytmy kwantowe [Quantum algorithms; in Polish]. WSiP, Warszawa. Search in Google Scholar

Lago, J., Marcjasz, G., De Schutter, B. and Weron R. (2021) Forecasting Day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark. Applied Energy, 293. Search in Google Scholar

Mrozek, B. and Mrozek, Z. (2010) Matlab i Simulink: poradnik użytkownika [Matlab and Simulink: user’s guide; in Polish]. Helion, Gliwice. Search in Google Scholar

Mielczarski, W. (2000) Rynki energii elektrycznej. Wybrane aspekty techniczne i ekonomiczne [Electric energy markets. Selected technical and economic aspects; in Polish]. ARE S.A. i Energoprojekt-Consulting S.A., Warszawa. Search in Google Scholar

Nazarko, J. (2018) Prognozowanie w zarządzaniu przedsiębiorstwem. Część IV. Prognozowanie na podstawie modeli trendu [Forecasting in enterprise management. Part IV. Forecasting on the basis of trend models; in Polish]. Politechnika Bia lostocka, Bia lystok. Search in Google Scholar

Osowski, S. (2020) Sztuczne sieci neuronowe do przetwarzania informacji [Artificial neural networks for information processing; in Polish]. OW PW, Warszawa. Search in Google Scholar

Ruciński, D. (2018) Modelowanie neuronalne cen na Towarowej Giełdzie Energii Elektrycznej wspomagane algorytmem ewolucyjnym oraz inspirowane obliczeniami kwantowymi [Neural modeling of prices on Electric Power Exchange supported with evolutionary algorithm and inspired by quantum calculations; in Polish]. Doctoral dissertation elaborated under the guidance of Professor Jerzy Tchórzewski, UPH in Siedlce, IBS PAN, Warszawa. Search in Google Scholar

Ruciński, D. (2019) The Influence of the Artificial Neural Network Type on the Quality of Learning on the Day-Ahead Market Model at Polish Electricity Exchange Join-Stock Company. Studia Informatica. System and Information Technology, 1-2(23), 77-93. Search in Google Scholar

Ruciński, D. (2022) The impact of the size of the training set on the predictive abilities of neural models on the example of the Day-Ahead Market System of TGE S.A. Studia Informatica. Systems and Information Technology, 1(26)/2022, 5-24. Search in Google Scholar

Sawerwain, M. and Wiśniewska, J. (2015) Informatyka kwantowa. Wybrane obwody i algorytmy [Quantum informatics. Selected circuits and algorithms; in Polish]. PWN, Warszawa. Search in Google Scholar

Tchórzewski, J. (2013) Rozwój systemu elektroenergetycznego w ujęciu teorii sterowania i systemów [Development of the electric power system in the perspective of control and systems theory; in Polish]. OW PWr., Wrocław. Search in Google Scholar

Tchórzewski, J. (2021) Metody sztucznej inteligencji i informatyki kwantowej w ujęciu teorii sterowania i systemów [Methods of artificial intelligence and quantum mechanics in the light of control and systems theory; in Polish]. Wydawnictwo Naukowe UPH w Siedlcach. Search in Google Scholar

Tchórzewski, J. and Ruciński, D. (2016) Quantum inspired evolutionary algorithm to improve parameters of neural models on example of Polish electricity power exchange. Electric Power Networks (EPNet), 1-8, doi: 10.1109/EPNET.2016.7999349. Search in Google Scholar

Tchórzewski, J. and Ruciński, D. (2018) Quantum-inspired Artificial Neural Networks and Evolutionary Algorithms Methods Applied to Modeling of the Polish Electric Power Exchange Using the Day-ahead Market Data. Information Systems in Management, 7, 3, 201–212. Search in Google Scholar

Tchórzewski, J. and Ruciński, D. (2019) Evolutionarily-Supported and Quantum-Inspired Neural Modeling Applied to the Polish Electric Power Exchange. Progress in Applied Electrical Engineering (PAEE), 1-8, doi: 10.1109/PAEE.2019.8788987. Search in Google Scholar

Wiśniewska, J., Sawerwain, M. and Obuchowicz, A. (2020) Basic quantum circuits for classification and approximation tasks. International Journal of Applied Mathematics and Computer Science, 30(4), 733–744. Search in Google Scholar

Wright, J. and Jordanov, I. (2017), Quantum inspired evolutionary algorithms with improved rotation gates for real-coded synthetic and real world optimization problems. Integrated Computer-Aided Engineering, 24, 3, 203-223. Search in Google Scholar

Ziel, F. and Weron, R. (2018) Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks. Energy Economics, Elsevier, 70(C), 396-420. Search in Google Scholar