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    Wyświetlanie 1-2 z 2
    Tytuł:
    Credibility Coefficients for Objects of Rough Sets
    Autorzy:
    Podraza, R.
    Dominik, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/92812.pdf
    Data publikacji:
    2006
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    data reliability
    credibility coefficient
    information system
    decision table
    rough sets
    artificial intelligence
    Opis:
    In this paper focus is set on data reliability. We propose a few methods, which calculate credibility coefficients for objects stored in decision tables. Credibility coefficient of object is a measure of its similarity with respect to the rest of the objects in the considered decision table. It can be very useful in detecting either corrupted data or abnormal and distinctive situations. It is assumed that the proper data appear in majority and can be separated from improper data by exploring mutual resemblance. The proposed methods take advantage of well known and widely used data mining technique - rough sets.
    Źródło:
    Studia Informatica : systems and information technology; 2006, 1(7); 93-104
    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 1-2 z 2

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