Akademik Veri Yönetim Sistemi
Mersin University Journal of Maritime Faculty, cilt.3, sa.1, ss.1-8, 2021 (Hakemli Dergi)
This study, which allows estimating main engine power of new ships based on data from general cargo ships, consists of
a series of mathematical relationships. Thanks to these mathematical relationships, it can be predicted main engine power
according to length (L), gross tonnage (GT) and age of a general cargo ship. In this study, polynomial regression, KNearest Neighbors (KNN) regression and Gradient Boosting Machine (GBM) regression algorithms are used. By this
means the relationships presented here, it is aimed to build ships that are environmentally friendly and can be sustained at
a lower cost by using the main engine power of the new ships with high accuracy. In addition, the relationships presented
here provide validation for computational fluid dynamics (CFDs) and other studies with empirical statements. As a
result of the study, polynomial regression gives similar results with other studies in the literature. We also concluded that
while KNN regression yields fast results, GBM regression algorithm provides more accurate solutions to estimate the
ship's main engine power.