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    Wyświetlanie 1-4 z 4
    Tytuł:
    The Influence of the Artificial Neural Network type on the quality of learning on the Day-Ahead Market model at Polish Power Exchange joint-stock company
    Autorzy:
    Ruciński, Dariusz
    Powiązania:
    https://bibliotekanauki.pl/articles/1819257.pdf
    Data publikacji:
    2019
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    Perceptron Artificial Neural Network
    Radial Artificial Neural Network
    Recursive Artificial Neural Network
    neural model quality
    Day-Ahead Market
    Polish Power Exchange
    Mean square error
    determination index
    Opis:
    The work contains the results of the Day-Ahead Market modeling research at Polish Power Exchange taking into account the numerical data on the supplied and sold electricity in selected time intervals from the entire period of its operation (from July 2002 to June 2019). Market modeling was carried out based on three Artificial Neural Network models, ie: Perceptron Artificial Neural Network, Recursive Artificial Neural Network, and Radial Artificial Neural Network. The examined period of the Day-Ahead Market operation on the Polish Power Exchange was divided into sub-periods of various lengths, from one month, a quarter, a half a year to the entire period of the market's operation. As a result of neural modeling, 1,191 models of the Market system were obtained, which were assessed according to the criterion of the least error MSE and the determination index R2.
    Źródło:
    Studia Informatica : systems and information technology; 2019, 1-2(23); 77--93
    1731-2264
    Pojawia się w:
    Studia Informatica : systems and information technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    GPU-based multi-layer perceptron as efficient method for approximation complex light models in per-vertex lighting
    Autorzy:
    Pietras, K.
    Rudnicki, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/92844.pdf
    Data publikacji:
    2005
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    sky color
    lighting model
    GeForce FX
    neural network
    GPU
    graphics processing unit
    Opis:
    This paper describes a display method of the sky color on GeForce FX hardware. Lighting model used here is taken from “Display of the Earth taking into account atmospheric scattering” by Tomoyuki Nishita et.al., however this model is not the only suitable one in the proposed method.
    Źródło:
    Studia Informatica : systems and information technology; 2005, 2(6); 53-63
    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:
    Comparative Study of the Identification Methods of the Management System of the Day-Ahead Market of Polish Energy Market S.A.
    Autorzy:
    Marlęga, Radosław
    Powiązania:
    https://bibliotekanauki.pl/articles/2052421.pdf
    Data publikacji:
    2021
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    artificial neural network
    business intelligence
    day ahead market
    Identification methods
    information system in management
    parametrical model
    Polish Energy Market
    Opis:
    Nowadays, identification and neural methods are used more and more often in modeling IT forecasting systems in addition to analytical methods. Six characteristic models used to forecast the Day- Ahead Market system functioning as a transaction management system at the Polish Power Exchange (POLPX) and the Nord Pool Spot market have been selected for comparative analysis. The research was preceded by a detailed discussion of modern criteria used to assess the quality of model fitting to the system, namely: effectiveness, efficiency, and robustness. In the literature, there are two main groups of system modeling methods, namely time series modeling methods and identification modeling methods, including neural modeling methods. Modeling usually results in such models as parametric models and artificial neural networks learned neural models of the Day-Ahead Market, as well as time series models, among others. In the comparative analysis, special attention was paid to the accuracy of the obtained models concerning the system. It has been pointed out that the studied solutions used to measure the accuracy of modeling criteria such as accuracy of fit or efficiency, and did not use the modeling efficiency, which is very important in IT forecasting systems for such large markets as the Day-Ahead Market of POLPX. The search for the best market models, including identification models of the Day- Ahead Market operation that can be used in electricity price forecasting is a very important issue both from the point of view of algorithmic solutions and economical solutions.
    Źródło:
    Studia Informatica : systems and information technology; 2021, 1-2(25); 67-86
    1731-2264
    Pojawia się w:
    Studia Informatica : systems and information technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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