2023
DOI: 10.1016/j.oceaneng.2022.111322
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Optimum trim prediction for container ships based on machine learning

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Cited by 8 publications
(5 citation statements)
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“…Data noise refers to inaccuracies introduced by sample selection and measuring area [37]. The random forests could use the randomness of the sample and feature set to efficiently train highly generalized models, which were relatively robust against data noise [38]. The BP neural networks, however, tended to be more vulnerable to outliers and other forms of data noise which may disturb classification and identification outcomes [39].…”
Section: Discussionmentioning
confidence: 99%
“…Data noise refers to inaccuracies introduced by sample selection and measuring area [37]. The random forests could use the randomness of the sample and feature set to efficiently train highly generalized models, which were relatively robust against data noise [38]. The BP neural networks, however, tended to be more vulnerable to outliers and other forms of data noise which may disturb classification and identification outcomes [39].…”
Section: Discussionmentioning
confidence: 99%
“…Data noise refers to inaccuracies introduced causing by sample selection and measuring area [26]. The random forests could use randomness of the sample and feature set to efficiently trained highly generalized models, which were relatively robust against data noise [27]. BP neural networks, however, tended to be more vulnerable to outliers and other forms of data noise which may disturb classification and identification outcomes [28].…”
Section: Discussionmentioning
confidence: 99%
“…There are three general conditions when a ship is sailing, namely even keel, trim by head, and trim by stern. Ships that experience abnormal trim will worsen conditions while sailing [12]. So that fatal losses in the ship-building process can be avoided as early as possible, namely by conducting a study of the freeboard and trim of converting ships, the hypothesis of this study is to calculate the two values (freeboard and trim) of conversion ships and assess whether they are still included in the standard of a decent ship or not.…”
Section: Introductionmentioning
confidence: 99%