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    Wyświetlanie 1-6 z 6
    Tytuł:
    Artificial Neural Network based on mathematical models used in quantum computing
    Autorzy:
    Ruciński, Dariusz
    Powiązania:
    https://bibliotekanauki.pl/articles/2201614.pdf
    Data publikacji:
    2022
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    neural modeling
    Day-Ahead Market
    Polish Power Exchange
    Hilbert space
    quantum inspired neural network
    Opis:
    The article is a proposition of a new approach to building a neural model based on the system of Day-Ahead Market operating at TGE S.A. The reason for the proposed method is an attempt to find a better model for the DAM system. The proposed methodology is based on using mathematical models used in quantum computing. All calculations performed on learning the Artificial Neuron Network are based on operations described in Hilbert space. The main idea of calculations is to replace the data from the decimal system into the quantum state in Hilbert space and perform learning operations for a neural model of the DAM system in a special manner which relay on the teaching model for each position of the quantum register for all data. The obtained results were compared to the “classical” neural model with the use of a comparative model.
    Źródło:
    Studia Informatica : systems and information technology; 2022, 2(27); 27--48
    1731-2264
    Pojawia się w:
    Studia Informatica : systems and information technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    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.
    Autorzy:
    Ruciński, Dariusz
    Powiązania:
    https://bibliotekanauki.pl/articles/2175162.pdf
    Data publikacji:
    2022
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    Day Ahead Market
    MATLAB environment
    Simulink environment
    neural modeling
    prediction time
    electricity prices
    Opis:
    The main object of the research was to examine the acceptable time horizon that could be predicted by previously learned models of the Day-Ahead Market (DAM) TGE S.A. system. The article contains the results of research on the predicting ability of different ANN models of the DAM TGE S.A. The research was conducted based on data covering the operation of the Polish stock exchange in the period from 2002 to 2019 (the first half of the year). The research was carried out based on the learned ANN models of the DAM system. Data were taken for examination covering the time from 2002 to 2019 (1st half of the year) and was divided into a different period, i.e., a month, a quarter, and a half-year., year, etc. The MSE, MAE, MAPE, and R2 were adopted as the criteria for assessing the ability of individual models to predict electricity prices. The research was carried out by successively expanding forecasting periods in a rolling manner. For example, for a half-year, prediction time intervals were increased from one week to month, two months, quarter, half-year, etc. results for a model representing a given period. A lot of interesting research results were obtained.
    Źródło:
    Studia Informatica : systems and information technology; 2022, 1(26); 5--22
    1731-2264
    Pojawia się w:
    Studia Informatica : systems and information technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Quantum inspiration to build a neural model based on the Day-Ahead Market of the Polish Power Exchange
    Autorzy:
    Ruciński, Dariusz
    Powiązania:
    https://bibliotekanauki.pl/articles/2052430.pdf
    Data publikacji:
    2021
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    Neural Modeling
    day-ahead market
    Polish power exchange
    mean square error
    determination index
    quantum inspired neural model
    Opis:
    The article is an attempt of the methodological approach to the proposed quantum-inspired method of neural modeling of prices quoted on the Day-Ahead Market operating at TGE S.A. In the proposed quantum-inspired neural model it was assumed, inter alia, that it is composed of 12 parallel Perceptron ANNs with one hidden layer. Moreover, it was assumed that weights and biases as processing elements are described by density matrices, and the values flowing through the Artificial Neural Network of Signals are represented by qubits. Calculations checking the correctness of the adopted method and model were carried out with the use of linear algebra and vector-matrix calculus in MATLAB and Simulink environments. The obtained research results were compared to the results obtained from the neural model with the use of a comparative model.
    Źródło:
    Studia Informatica : systems and information technology; 2021, 1-2(25); 23-37
    1731-2264
    Pojawia się w:
    Studia Informatica : systems and information technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prediction capabilities of the LSTM and Perceptron models based on the Day-Ahead Market on the Polish Power Exchange S.A.
    Autorzy:
    Ruciński, Dariusz
    Powiązania:
    https://bibliotekanauki.pl/articles/27323577.pdf
    Data publikacji:
    2023
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    shallow networks
    deep networks
    Day-Ahead Market
    MATLAB
    Simulink environment
    neural modeling
    prediction time
    electricity prices
    Opis:
    The main purpose of the research was to examine the properties of models for two kinds of neural networks, a deep learning models in which the Long Short-Term Memory was chosen and shallow neural model in which the Perceptron Neural Network was chosen. The subject of the examination was the Day-Ahead Market system of PPE S.A. The article presents the learning results of both networks and the results of the predictive abilities of the models. The research was conducted based on data published on the Polish Stock Exchange for the 2018 year. The MATLAB environment was chosen as a tool for providing the examinations. The determination index (R2) and the mean square error (MSE) was adopted as the network evaluation criterion for the learning ability and for the prediction ability of both networks.
    Źródło:
    Studia Informatica : systems and information technology; 2023, 1(28); 69--82
    1731-2264
    Pojawia się w:
    Studia Informatica : systems and information technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Correction of the parametric model of the Day-Ahead Market system using the Artificial Neural Network
    Autorzy:
    Marlęga, Radosław
    Powiązania:
    https://bibliotekanauki.pl/articles/2175158.pdf
    Data publikacji:
    2022
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    artificial neural network
    day-ahead market
    modeling
    simulation
    comparative research
    model sensitivity testing
    Opis:
    The paper shows that it is possible to correct the identification model of the Day-Ahead Market system by employing the Perceptron Artificial Neural Network. First, a simulation model of the DAM system at the POLPX has been built, and then it has been shown how the model can be corrected so that the weighted average electricity prices obtained are close enough to the exchange-quoted ones. Next, simulation, comparative and sensitivity studies of the model were carried out for forecast data for four characteristic hours: 6, 12, 18, and 24 of the following year. Many interesting research results were obtained, including a result of sensitivity testing it was shown that the obtained models can be used in forecasting studies.
    Źródło:
    Studia Informatica : systems and information technology; 2022, 1(26); 85--105
    1731-2264
    Pojawia się w:
    Studia Informatica : systems and information technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Neural model of human gait and its implementation in MATLAB and Simulink Environment using Deep Learning Toolbox
    Autorzy:
    Tchórzewski, Jerzy
    Wielgo, Arkadiusz
    Powiązania:
    https://bibliotekanauki.pl/articles/2052427.pdf
    Data publikacji:
    2021
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    artificial neural network
    deep learning toolbox
    humanoid robots
    MATLAB environment
    Simulink environment
    modeling of human walking motion
    Opis:
    The article presents selected results of research on the modeling of humanoid robots, including the results of neural modeling of human gait and its implementation in the environment MATLAB and Simulink with the use of Deep Learning Toolbox. The subject of the research was placed within the scope of the available literature on the subject. Then, appropriate research experiments on human movement along a given trajectory were developed. First, the method of measuring the parameters present in the experiment was established, i.e. input quantities (displacement of the left heel, displacement of the right heel) and output quantities (displacement of the measurement point of the human body in space). Then, research experiments were carried out, as a result of which numerical data were measured in order to use them for teaching and testing the Artificial Neural Network. The Perceptron Artificial Neural Network architecture was used to build a model of a neural human walk along a given trajectory. The obtained results were discussed and interpreted, drawing a number of important conclusions.
    Źródło:
    Studia Informatica : systems and information technology; 2021, 1-2(25); 39-65
    1731-2264
    Pojawia się w:
    Studia Informatica : systems and information technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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