PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Statistical Modelling for Ship Propulsion Efficiency
JP Petersen, DJ Jacobsen and Ole Winther
J. of Marine Science and Technology 2011.


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.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Multimodal Integration
ID Code:9234
Deposited By:Ole Winther
Deposited On:21 February 2012