Research on Cooling Load of Central Air Conditioning System for Cruise Ship

Taking cruise ships as the research object, this study establishes models of the main types of cabins and public areas on cruise ships using the TRNSYS simulation platform. Apply the corresponding dynamic meteorological parameters on the cruise route to the established model and output hourly load data of summer cruise ships. The Pearson correlation analysis method is used to determine input variables and obtain the original dataset. Various representative intelligent algorithms are selected for training and prediction. The results show that the Random Forest algorithm performs best, providing a reference for subsequent energy-saving operation and fault diagnosis of cruise ship air conditioning systems.