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Wyszukujesz frazę "Kwaśnicka, H." wg kryterium: Autor

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    Wyświetlanie 1-4 z 4
    Tytuł:
    Efficiency of selected meta-heuristics applied to the TSP problem: a simulation study
    Autorzy:
    Kwaśnicka, H.
    Powiązania:
    https://bibliotekanauki.pl/articles/1931573.pdf
    Data publikacji:
    2003
    Wydawca:
    Politechnika Gdańska
    Tematy:
    ant colony
    genetic algorithms
    simulated annealing
    tabu search
    neural networks
    Opis:
    The paper presents a simulation study of the usefulness of a numberof meta-heuristicsused as optimisation methods forTSPproblems. The five considered approaches are outlined: GeneticAlgorithm, Simulated Annealing, Ant Colony System, Tabu Search and Hopfield Neural Network.Using a purpose-developed computer program, efficiency of the meta-heuriticshas been studied andcompared. Results obtained from about 40000 simulation runs are briefly presented and discussed.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2003, 7, 1; 73-91
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    EMOT - an evolutionary approach to 3D computer animation
    Autorzy:
    Kwaśnicka, H.
    Woźniak, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/1943270.pdf
    Data publikacji:
    2007
    Wydawca:
    Politechnika Gdańska
    Tematy:
    gene expression programming
    computer animation
    simulation
    motion
    Opis:
    Key-framing and Inverse Kinematics are popular animation methods, but new approaches are still developed. We propose a new evolutionary method of creating animation - the EMOT (Evolutionary MOTion) system. It enables automation of motion of animated characters and uses a new evolutionary approach - Gene Expression Programming (GEP). Characters are controlled by computer programs, an animator providing the way of motion's evaluation. GEP works with a randomly selected initial population, using directed but random selection. Experiments have shown that the proposed method is capable of developing robust controllers.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2007, 11, 1-2; 71-86
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Correlation-based feature selection strategy in classification problems
    Autorzy:
    Michalak, K.
    Kwaśnicka, H.
    Powiązania:
    https://bibliotekanauki.pl/articles/908379.pdf
    Data publikacji:
    2006
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    selekcja cech
    współzależność cech
    klasyfikacja
    feature selection
    pairwise feature evaluation
    feature correlation
    pattern classification
    Opis:
    In classification problems, the issue of high dimensionality, of data is often considered important. To lower data dimensionality, feature selection methods are often employed. To select a set of features that will span a representation space that is as good as possible for the classification task, one must take into consideration possible interdependencies between the features. As a trade-off between the complexity of the selection process and the quality of the selected feature set, a pairwise selection strategy has been recently suggested. In this paper, a modified pairwise selection strategy is proposed. Our research suggests that computation time can be significantly lowered while maintaining the quality of the selected feature sets by using mixed univariate and bivariate feature evaluation based on the correlation between the features. This paper presents the comparison of the performance of our method with that of the unmodified pairwise selection strategy based on several well-known benchmark sets. Experimental results show that, in most cases, it is possible to lower computation time and that with high statistical significance the quality of the selected feature sets is not lower compared with those selected using the unmodified pairwise selection process.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2006, 16, 4; 503-511
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Evolutionary approach to rule extraction from medical data
    Autorzy:
    Kwaśnicka, H.
    Markowska-Kaczmar, U.
    Osojca, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/333717.pdf
    Data publikacji:
    2004
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    ekstrakcja reguł
    obliczenia ewolucyjne
    rule extraction
    evolutionary computation
    Opis:
    In the paper the method called CGA based on a cooperating genetic algorithm is presented. The CGA is developed for searching a set of rules describing classes in classification problems on the basis of training examples. The details of the method, such as a schema of coding (a chromosome), and a fitness function are shortly described. The method is independent of the type of attributes and it allows choosing different evaluation functions. Developed method was tested using different benchmark data sets. Next, in order to evaluate the efficiency of CGA, it was tested using the Breast Cancer data set with 10 fold cross validation technique.
    Źródło:
    Journal of Medical Informatics & Technologies; 2004, 7; KB3-12
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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