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http://dx.doi.org/10.3744/SNAK.2020.57.5.305

Probabilistic Time Series Forecast of VLOC Model Using Bayesian Inference  

Son, Jaehyeon (Department of Naval Architecture and Ocean Engineering, College of Engineering, INHA University)
Kim, Yooil (Department of Naval Architecture and Ocean Engineering, College of Engineering, INHA University)
Publication Information
Journal of the Society of Naval Architects of Korea / v.57, no.5, 2020 , pp. 305-311 More about this Journal
Abstract
This study presents a probabilistic time series forecast of ship structural response using Bayesian inference combined with Volterra linear model. The structural response of a ship exposed to irregular wave excitation was represented by a linear Volterra model and unknown uncertainties were taken care by probability distribution of time series. To achieve the goal, Volterra series of first order was expanded to a linear combination of Laguerre functions and the probability distribution of Laguerre coefficients is estimated using the prepared data by treating Laguerre coefficients as random variables. In order to check the validity of the proposed methodology, it was applied to a linear oscillator model containing damping uncertainties, and also applied to model test data obtained by segmented hull model of 400,000 DWT VLOC as a practical problem.
Keywords
Volterra series; Laguerre polynomials; Impulse response function; Bayesian linear regression model; VLOC; Vertical bending moment;
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Times Cited By KSCI : 1  (Citation Analysis)
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