Refined Predictive Equations for Modern Bulk Carriers

Empirical predictive equations for principal particulars of modern bulk carriers are developed using deadweight (DWT) as the sole primary predictor. A curated dataset of 148 contemporary bulk carriers with a held-out test set of 20 vessels was used to fit and compare three model families: polynomial trendlines (up to fourth degree), power-law (log–log OLS), and multivariate linear regressions. Displacement computed from predicted particulars and an estimated block coefficient served as the principal validation metric. Power-law models delivered the best balance of accuracy and parsimony, yielding mean displacement percentage errors of approximately 0.07–4.97% on the test set. Data processing employed objective outlier diagnostics (standardized residuals, Cook’s distance, leverage) with imputation uncertainty propagated into aggregate error estimates. The manuscript provides explicit formulae, diagnostic statistics, and sensitivity analyses, and specifies calibrated application ranges. These empirical relations are intended for preliminary naval-architectural sizing and fleet-scale assessments, subject to the documented limits on extrapolation and cohort heterogeneity.