4.6 Article

White-Black-Box Hybrid Model Identification Based on RM-RF for Ship Maneuvering

期刊

IEEE ACCESS
卷 7, 期 -, 页码 57691-57705

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2914120

关键词

Modeling; machine learning algorithms; hybrid intelligent systems; motion estimation; system identification

资金

  1. National Natural Science Foundation of China [51579025]
  2. Liaoning National Natural Science Foundation [20170540090]
  3. Fundamental Research Funds for the Central Universities [3132018306]

向作者/读者索取更多资源

A new system identification scheme based on model reference and random forest (RM-RF), was used to model ship maneuvering. First, the scheme establishes the relationship between a ship and the RM using the similarity rule. Second, a suitable RM was selected from public ship maneuvering models to avoid the tuning process in the empirical Maneuvering Modeling Group (MMG), model. Third, RF creates a relationship to map accelerations between the ship and the RM. Finally, the study case was implemented with fewer free-running model test data. The results show the feasibility of the identification modeling scheme and validated the generalizability of the proposed approach.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据