Analysis of ship voyage data based on Chow-Liu tree augmented Na ̈ıveBayes-method to support biofouling management

• Autores: Elias Altarriba, Justiina Halonen
• Localización: Journal of maritime research: JMR, ISSN 1697-4840, Vol. 17, Nº. 3, 2020, págs. 47-54
• Idioma: inglés
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• Resumen

  • The Baltic Sea is a sensitive marine environment and a unique brackish water basin. In spite of environ-mental protection policies of its coastal states, the sea is still under unsustainable load. Environmentalimpact of shipping is one of the concerns, as the area is a major transport corridor for both passengersand cargo. Many restrictions and environmental regulations direct the shipowners actions. However,there is still issues yet too complicated to be regulated by laws. One such an issue is the spreading ofharmful invasive species. In order to gather more data that the future regulations can be based on, the EUInterreg Baltic Sea Region programme funded a multinational research project called “COMPLETE”.Ballast waters are well known pathways for invasive species, but migration by immersed hull struc-tures is a lesser known vector. The role of the South-Eastern Finland University of Applied Sciencesin the project is to conduct onboard measurements and data collection on ships’ performance. The datais collected 2018. . . 2019 during normal operation of the ships, and consists of information extractedfrom voyage data; shaft power, fuel consumption, propeller pitches and rotation speeds, trim, draught,DWT, speed over ground, AIS data and weather conditions provided by coastal meteorological stations.The aim is to demonstrate on individual ship level the impact of biofouling on resistances and fuelconsumption, and, in consequence, increase the shipowners’ motivation to keep immersed hulls cleanand thus save fuel, reduce gaseous emissions and prevent the spreading of invasive species. However,causation network of collected data includes powerful mixers such as weather conditions. The objectiveof this paper is to present experiences of utilizing Chow-Liu tree augmented Na ̈ıve Bayes formulationfor analysing the voyage data. The method is computationally efficient and usually gives quite reliableresults even if the collected data contains a lot of noise or inadequacies