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Wyszukujesz frazę "neural modeling" wg kryterium: Temat

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    Wyświetlanie 1-3 z 3
    Tytuł:
    On the application of the artificial neural network method to a neural simulator of steam turbine power plant
    Autorzy:
    Ślęzak-Żołna, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/259627.pdf
    Data publikacji:
    2006
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    siłownie turbinowe
    modelowanie i symulacja
    elektrownie turbinowe
    diagnostyka bieżąca
    neural modeling and simulating
    turbine power plants
    on-line diagnostics
    Opis:
    In the paper a neural simulator of steam power unit is presented as an example of application of artificial neural networks (ANN) for modeling complex technical objects. A set of one-directional back-propagation networks was applied to simulate distribution of main steam flow parameters in the cycle's crucial points for a broad range of loading. A very good accuracy and short computation time was obtained. The advantages make the simulator useful for on-line diagnostic applications where short response time is very important. The most important features of the simulator, main phases of its elaboration and a certain amount of experience gained from solving the task was presented to make the practical application of the method in question more familiar.
    Źródło:
    Polish Maritime Research; 2006, 1; 16-20
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Research on the risk classification of cruise ship fires based on an attention-BP neural network
    Autorzy:
    Xiong, Zhenghua
    Xiang, Bo
    Chen, Ye
    Chen, Bin
    Powiązania:
    https://bibliotekanauki.pl/articles/32912853.pdf
    Data publikacji:
    2022
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    cruise fire
    simulation modeling
    ensemble learning
    BP neural network
    Opis:
    Due to the relatively closed environment, complex internal structure, and difficult evacuation of personnel, it is more difficult to prevent ship fires than land fires. In this paper, taking the large cruise ship as the research object, the physical model of a cruise cabin fire is established through PyroSim software, and the safety indexes such as smoke temperature, CO concentration, and visibility are numerically simulated. An Attention-BP neural network model is designed for realizing the intelligent identification of a cabin fire and dividing the risk level, which integrates the diagnosis results of multiple neural network models through the self-Attention mechanism and adaptively distributes the weight of each BP neural network model. The proposed model can provide decision-making reference for subsequent fire-fighting measures and personnel evacuation. Experimental results show that the proposed Attention-BP neural network model can effectively realize the early warning of the fire risk level. Compared with other machine learning algorithms, it has the highest stability and accuracy and reduces the uncertainty of early cabin fire warning.
    Źródło:
    Polish Maritime Research; 2022, 3; 61-68
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    On the modeling of car passenger ferryship design parameters with respect to selected sea-keeping qualities and additional resistance in waves
    Autorzy:
    Cepowski, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/258828.pdf
    Data publikacji:
    2009
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    sea-keeping qualities
    roll-on/roll-off ferryship
    rolling
    motion sickness index
    lateral accelerations
    additional resistance in waves
    ship design parameters
    modeling
    artificial neural networks
    optimization
    Pareto method
    Opis:
    This paper presents the modeling of car passenger ferryship design parameters with respect to such design criteria as selected sea-keeping qualities and additional resistance in waves. In the first part of the investigations approximations of selected statistical parameters of design criteria of ferryship were elaborated with respect to ship design parameters. The approximation functions were obtained with the use of artificial neural networks. In the second part of the investigations design solutions were searched for by applying the singleand multi-criterial optimization methods. The multi-criterial optimization was performed by using Pareto method. Such approach made it possible to present solutions in such form as to allow decision makers (shipowner, designer) to select solutions the most favourable in each individual case.
    Źródło:
    Polish Maritime Research; 2009, 3; 3-10
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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