Journal
IEEE ACCESS
Volume 7, Issue -, Pages 57691-57705Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2914120
Keywords
Modeling; machine learning algorithms; hybrid intelligent systems; motion estimation; system identification
Categories
Funding
- National Natural Science Foundation of China [51579025]
- Liaoning National Natural Science Foundation [20170540090]
- Fundamental Research Funds for the Central Universities [3132018306]
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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.
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