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.

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.

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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