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    Active Learning–Based Estimation of Extreme Roll Motion in Beam Seas with Supervised Dimensionality Reduction and Gradient Approximation

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    AJRUA6.RUENG-1756.pdf (1.455Mb)
    Date
    2026
    Author
    Takami, Tomoki
    Kitahara, Masaru
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    Abstract
    AbstractAn efficient method is presented for estimating extreme nonlinear roll motion of a ship in beam seas in a given short-term sea state. With the aim of reducing the number of numerical simulations for roll motion simulation, this study employs an ...
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    http://yetl.yabesh.ir/yetl1/handle/yetl/4314431
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    • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

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