2017 · 12 citations · 14 references
ComputingComputer ScienceEconomicsDemand ForecastingQuantum ComputingQuantum MechanicsNeural ModelingNeural NetworksQuantum ComputationQuantum Machine LearningQuantum SimulationArtificial Neural Network SurrogatesDay-ahead Electricity MarketsNeural Network ModelingQuantum Neural NetworksSimulink Models
The paper presents results of research on the improvement of parameters of the neural model of system of the Polish Electricity Stock Exchange in the MATLAB and Simulink environment using methods inspired by quantum computer science. The models of the Artificial Neural Network of the taught Electricity Stock Exchange System, including selected elements of quantum computing used to improve the neural model of this system, and the Electricity Stock Exchange System quantum-neural model were also shown. Particular attention has been paid to neural modeling using Neural Network Toolbox and quantum-neural modeling using Simulink. The research experiments were carried out on the basis of quotations on the Polish Electricity Stock Exchange for quotes on the Day Ahead Market. As input quantities in the learning process of the Artificial Neural Network, the volume of electricity supplied and sold at particular times of the day was used, and the average prices received at each of the 24 hours as a starting point. As a result of the learning, a neural model of Electricity Stock Exchange System in the form of an Artificial Neural Network was obtained, and on its quantum-neuronal model of Electricity Stock Exchange system, which used the quantum calculations simulated in Simulink.
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