Estimation of Tanker Ships’ Lightship Displacement Using Multiple Linear Regression and XGBoost Machine Learning

It is of the utmost importance to accurately estimate different ships’ weights during their design stages. Additionally, lightship displacement (LD) data are not always easily accessible shipping stakeholders, while other dimensions within hand’s reach (for example, through from online Automatic Identification System (AIS)). Therefore, determining might be a difficult task, and it traditionally performed with help mathematical equations developed by shipbuilders. Distinct traditional approach, this study offers possibility employing machine learning methods weight as possible. This paper estimates oil tankers’ using two dimensions, length overall, breadth. The tanker ships were collected INTERTANKO Chartering Questionnaire Q88, available online, and, because similar block coefficients, all sizes used for estimation. Furthermore, multiple linear regression extreme gradient boosting (XGBoost) utilised displacement. Results show that XGBoost provide results, both could powerful tools estimating types ships.