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    Wyświetlanie 1-6 z 6
    Tytuł:
    Genetic tuning fuzzy dempster-shafer decision rules
    Autorzy:
    Walijewski, J. S.
    Sosnowski, Z. A.
    Powiązania:
    https://bibliotekanauki.pl/articles/1931591.pdf
    Data publikacji:
    2002
    Wydawca:
    Politechnika Gdańska
    Tematy:
    genetic algorithms
    fuzzy modelling
    Dempster-Shafer theory
    Opis:
    The objective of this paper is to employ the Dempster-Shafer theory (DST) as a vehicle supporting the generation of fuzzy decision rules. The concept of fuzzy granulation realized via fuzzy clustering is aimed at the discretization of continuous attributes. Next we use Genetic for tuning fuzzy decision rules. Detailed experimental studies are presented concerning well-known medical data sets available on the Web.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2002, 6, 4; 631-640
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Rotor blade geometry optimization in kaplan turbine
    Autorzy:
    Banaszek, M.
    Tesch, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/1943215.pdf
    Data publikacji:
    2010
    Wydawca:
    Politechnika Gdańska
    Tematy:
    fluid mechanics
    turbomachinery
    genetic algorithms
    artificial neural networks
    Opis:
    This paper presents a description of the method and results of rotor blade shape optimization. The rotor blading constitutes a part of a turbine’s flow path. The optimization consists in selecting a shape that minimizes the polytrophic loss ratio [1]. The shape of the blade is defined by the mean camber line and thickness of the airfoil. The thickness is distributed around the camber line based on the ratio of distribution. A global optimization was done by means of Genetic Algorithms (GA) with the help of Artificial Neural Networks (ANN) for approximations. For the numerical simulation of a flow through the model Kaplan turbine, the geometry employed in the model was based on the actual geometry of the existing test stage. The fluid parameters and the boundary conditions for the model were based on experimental measurements which were carried out at the test stand at the Department of Turbomachinery and Fluid Mechanics at the Gdansk University of Technology. The shape of the blading was optimized for the operational point with a maximum efficiency.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2010, 14, 3; 209-225
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Voice command recognition using hybrid genetic algorithm
    Autorzy:
    Wroniszewska, M.
    Dziedzic, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/1955309.pdf
    Data publikacji:
    2010
    Wydawca:
    Politechnika Gdańska
    Tematy:
    voice command recognition
    genetic algorithms
    K-nearest neighbour
    hybrid approach
    Opis:
    Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer system). This paper describes the construction of a model for a voice command recognition system based on the combination of genetic algorithms (GAs) and K-nearest neighbour classifier (KNN). The model consists of two parts. The first one concerns the creation of feature patterns from spoken words. This is done by means of the discrete Fourier transform and frequency analysis. The second part constitutes the essence of the model, namely the design of the supervised learning and classification system. The technique used for the classification task is based on the simplest classifier – K-nearest neighbour algorithm. GAs, which have been demonstrated as a good optimization and machine learning technique, are applied to the feature extraction process for the pattern vectors. The purpose and main interest of this work is to adapt such a hybrid approach to the task of voice command recognition, develop an implementation and to assess its performance. The complete model of the system was implemented in the C++ language, the implementation was subsequently used to determine the relevant parameters of the method and to improve the approach in order to obtain the desired accuracy. Different variants of GAs were surveyed in this project and the influence of particular operators was verified in terms of the classification success rate. The main finding from the performed numerical experiments indicates the necessity of using genetic algorithms for the learning process. In consequence, a highly accurate recognition system was obtained, providing 94.2% correctly classified patterns. The hybrid GA/KNN approach constituted a significant improvement over the simple KNN classifier. Moreover, the training time required for the GA to learn the given set of words was found to be on a level that is acceptable for the efficient functioning of the voice command recognition system.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2010, 14, 4; 377-396
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    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:
    A parallel genetic algorithm for creating virtual portraits of historical figures
    Autorzy:
    Krawczyk, H.
    Proficz, J.
    Ziółkowski, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/1933983.pdf
    Data publikacji:
    2012
    Wydawca:
    Politechnika Gdańska
    Tematy:
    genetic algorithms
    fitness function
    KASKADA platform
    parallel processing
    high performance computing
    Opis:
    In this paper we present a genetic algorithm (GA) for creating hypothetical virtual portraits of historical figures and other individuals whose facial appearance is unknown. Our algorithm uses existing portraits of random people from a specific historical period and social background to evolve a set of face images potentially resembling the person whose image is to be found. We then use portraits of the person’s relatives to judge which of the evolved images are most likely to resemble his/her actual appearance. Unlike typical GAs, our algorithm uses a new supervised form of fitness function which itself is affected by the evolution process. Additional description of requested facial features can be provided to further influence the final solution (i.e. the virtual portrait). We present an example of a virtual portrait created by our algorithm. Finally, the performance of a parallel implementation developed for the KASKADA platform is presented and evaluated.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2012, 16, 1-2; 145-162
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The identification of the boundary geometry with corner points in inverse two-dimensional potential problems
    Autorzy:
    Zieniuk, E.
    Gabrel, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/1931586.pdf
    Data publikacji:
    2002
    Wydawca:
    Politechnika Gdańska
    Tematy:
    inverse boundary value problem
    boundary geometry identification
    geometry
    parametric integral equation system
    finite element method
    boundary element method
    evolution algorithm
    genetic algorithms
    Opis:
    The paper presents fragment of a larger study concerning the effective methods of solving the inverse boundary value problems. The boundary value problem described here is formulated as a problem of the identification of a boundary geometry with corner points. A method using a parametric integral equations system (PIES) is proposed. PIES used in the method makes the easy modelling of the geometry with corner points possible. This effect is obtained by the application of modified splines. An evolution algorithm is used for the effective control of modifications of the boundary geometry. Some experimental tests of the efficiency of the discussed method were performed for two-dimensional inverse potential problems.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2002, 6, 4; 651-660
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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