Prediction of Ship Main Particulars for Harbor Tugboats Using a Bayesian Network Model and Non-Linear Regression

Ömer Emre Karaçay, Çağlar Karatuğ, Tayfun Uyanık, Yasin Arslanoğlu, Abderezak Lashab*

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Dergiye katkıMakalebilirkişi

Özet

Determining the key characteristics of a ship during the concept and preliminary design phases is a critical and intricate process. In this study, we propose an alternative to traditional empirical methods by introducing a model to estimate the main particulars of diesel-powered Z-Drive harbor tugboats. This prediction is performed to determine the main particulars of tugboats: length, beam, draft, and power concerning the required service speed and bollard pull values, employing Bayesian network and non-linear regression methods. We utilized a dataset comprising 476 samples from 68 distinct diesel-powered Z-Drive harbor tugboat series to construct this model. The case study results demonstrate that the established model accurately predicts the main parameters of a tugboat with the obtained average of mean absolute percentage error values; 6.574% for the Bayesian network and 5.795%, 9.955% for non-linear regression methods. This model, therefore, proves to be a practical and valuable tool for ship designers in determining the main particulars of ships during the concept design stage by reducing revision return possibilities in further stages of ship design.

Orijinal dilİngilizce
Makale numarası2891
DergiApplied Sciences (Switzerland)
Hacim14
Basın numarası7
DOI'lar
Yayın durumuYayınlandı - Nis 2024

Bibliyografik not

Publisher Copyright:
© 2024 by the authors.

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