Evaluation of Ship Energy Efficiency Predictive and Optimization Models Based on Noon Reports and Condition Monitoring Datasets

摘要

For a long time, the shipping industry has relied on Noon Reports to extract the main parameters required to define both the ship's performance and fuel consumption, despite the fact that these reports have low sampling frequency (approx. 24 hours. Nowadays, satellite communications, telemetries, data collection, and analytics are making possible to treat a fleet of ships as a single unit. Thus, the shipping industry is definitely part of the information business. In the current work, we present a qualitative and quantitative comparison between the models developed from historical trends that are extracted from Noon Reports and the Continuous Monitoring System. The analysis is based on parameters that are reported by both data sources. While effort has been made in order to quantify variances due to the different sampling rate, our main focus was on quantification of uncertainty and the resulted confidence interv al in order to clarify the potential and limitations of the resulting predictive models. The paper aims to contribute to the areas of tools and mechanisms of data analytics, in the specific area of maritime intelligence.