Abstract
This paper presents a state-of-the-art systems approach to statistical modelling of fuel efficiency in ship propulsion, and also a novel and publicly available data set of high quality sensory data. Two statistical model approaches are investigated and compared: artificial neural networks and Gaussian processes (GP). The data presented is a publicly available full-scale data set, with a whole range of features sampled over a period of 2 months. We further discuss interpretations of the operational data in relation to the underlying physical system.
| Original language | English |
|---|---|
| Journal | Journal of Marine Science and Technology |
| Volume | 17 |
| Issue number | 1 |
| Pages (from-to) | 30-39 |
| ISSN | 0948-4280 |
| DOIs | |
| Publication status | Published - 2012 |
Keywords
- Vessel efficiency
- Artificial neural networks
- Gaussian processes
- Energy conservation
- Advisory systems
- Computer simulation
