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    Wyświetlanie 1-2 z 2
    Tytuł:
    Comprehensive Evaluation Cloud Model for Ship Navigation Adaptability
    Autorzy:
    Zhu, M.
    Wen, Y.
    Zhou, C.
    Xiao, C.
    Powiązania:
    https://bibliotekanauki.pl/articles/115973.pdf
    Data publikacji:
    2014
    Wydawca:
    Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
    Tematy:
    cloud computing
    Cloud Model
    marine navigation
    Delphi
    Qualitative Description
    Quantitative Transformation
    Cloud Algorithm
    Fuzzy Comprehensive Evaluation Method
    Opis:
    In this paper, using cloud model and Delphi, we build a comprehensive evaluation cloud model to solve the problems of qualitative description and quantitative transformation in ship navigation adaptability comprehensive evaluation. In the model, the normal cloud generator is used to find optimal cloud models of reviews and evaluation factors. The weight of each evaluation factor is determined by cloud model and Delphi. The floating cloud algorithm is applied to aggregate the bottom level’s evaluation factors, and comprehensive cloud algorithm is used to aggregate the highest level’s evaluation factors to get comprehensive evaluation cloud model. Finally, evaluation result is got by matching comprehensive evaluation cloud model and optimal cloud model of reviews. As case study, the model is applied to the small LNG ship’s navigation adaptability in Southeast Asia. Compared with the fuzzy comprehensive evaluation method, the model proposed in this paper is more intuitive and reliable in comprehensive evaluation of the small LNG ship’s navigation adaptability.
    Źródło:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2014, 8, 3; 331-336
    2083-6473
    2083-6481
    Pojawia się w:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Parameter identification of ship maneuvering models using recursive least square method based on support vector machines
    Autorzy:
    Zhu, M.
    Hahn, A.
    Wen, Y.
    Bolles, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/116455.pdf
    Data publikacji:
    2017
    Wydawca:
    Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
    Tematy:
    ship manoeuvering
    recursive least square method
    ship manoeuvering model
    ship maneuverability prediction
    Support Vector Machines (SVM)
    empirical mode decomposition (EMD)
    Computational Fluid Dynamics (CFD)
    Extended Kalman Filter (EKF)
    Opis:
    Determination of ship maneuvering models is a tough task of ship maneuverability prediction. Among several prime approaches of estimating ship maneuvering models, system identification combined with the full-scale or free- running model test is preferred. In this contribution, real-time system identification programs using recursive identification method, such as the recursive least square method (RLS), are exerted for on-line identification of ship maneuvering models. However, this method seriously depends on the objects of study and initial values of identified parameters. To overcome this, an intelligent technology, i.e., support vector machines (SVM), is firstly used to estimate initial values of the identified parameters with finite samples. As real measured motion data of the Mariner class ship always involve noise from sensors and external disturbances, the zigzag simulation test data include a substantial quantity of Gaussian white noise. Wavelet method and empirical mode decomposition (EMD) are used to filter the data corrupted by noise, respectively. The choice of the sample number for SVM to decide initial values of identified parameters is extensively discussed and analyzed. With de-noised motion data as input-output training samples, parameters of ship maneuvering models are estimated using RLS and SVM-RLS, respectively. The comparison between identification results and true values of parameters demonstrates that both the identified ship maneuvering models from RLS and SVM-RLS have reasonable agreements with simulated motions of the ship, and the increment of the sample for SVM positively affects the identification results. Furthermore, SVM-RLS using data de-noised by EMD shows the highest accuracy and best convergence.
    Źródło:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2017, 11, 1; 23-29
    2083-6473
    2083-6481
    Pojawia się w:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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