Abstract
Kyoto Protocol and competitiveness of the shipping market have been urging shipping companies to pay increasing attention to ship energy efficiency monitoring. At the same time, new monitoring data acquisition systems on modern ships have brought to a navigation data overload that have to be fully utilized via statistical methodologies. For this purpose, an empirical approach based on Partial Least-Squares regression is introduced by means of a real case study in order to give practical indications on CO2 emission control and for supporting prognosis of faults.
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The authors are grateful to the Grimaldi Group Energy Saving Department engineers Dario Bocchetti and Andrea D’Ambra.
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Lepore, A., Palumbo, B., Capezza, C. (2018). An Empirical Approach to Monitoring Ship CO\(_2\) Emissions via Partial Least-Squares Regression. In: Perna, C., Pratesi, M., Ruiz-Gazen, A. (eds) Studies in Theoretical and Applied Statistics. SIS 2016. Springer Proceedings in Mathematics & Statistics, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-319-73906-9_20
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