首页    期刊浏览 2024年11月28日 星期四
登录注册

文章基本信息

  • 标题:Bayesian Inference and Prediction of Wave-induced Ship Motion based on Discrete-frequency Model Approximations ⁎
  • 本地全文:下载
  • 作者:Justin M. Kennedy ; Jason J. Ford ; Francis Valentinis
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:29
  • 页码:104-109
  • DOI:10.1016/j.ifacol.2018.09.477
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this paper, we investigate the use of a discrete-frequency approximation for stochastic processes, modelling wave-induced ship motion and assess its prediction performance. The proposed estimator is obtained by adapting Bayesian spectral inference methods. We study the relationship between the lag window and the prediction performance and suggest a minimum requirement on window length for minimising the prediction error. We show an application to prediction of the pitch, heave, and roll motion from experiments of a scale-model container ship.
  • 关键词:KeywordsStatistical InferenceDetection AlgorithmsBayesian Inference
国家哲学社会科学文献中心版权所有