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A fuzzy logic modeling of measures addressing shipping CO2 emissions
Lema, E.; Karaganis, A.; Papageorgiou, E. (2017). A fuzzy logic modeling of measures addressing shipping CO2 emissions. Journal of Intelligent Systems 26(3): 439-455. https://dx.doi.org/10.1515/jisys-2015-0161
In: Journal of Intelligent Systems. WALTER DE GRUYTER GMBH: Berlin. ISSN 0334-1860, meer
Peer reviewed article  

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Trefwoord
    Marien/Kust
Author keywords
    Shipping; CO2 emissions; fuzzy logic; expert system; market-basedmechanisms

Auteurs  Top 
  • Lema, E.
  • Karaganis, A.
  • Papageorgiou, E.

Abstract
    This study presents a decision support tool that uses a fuzzy logic model of expert knowledge to assist in the decision-making process in the context of mitigating shipping CO2 emissions. The issue of selecting a market-based shipping CO2 emission mechanism, as they were presented by the International Maritime Organization (IMO), has generated much discussion over the last decade due to the complexity of the industry. We built a fuzzy logic system using the input and output variables as well as their range values that have been set from the IMO Expert Group study. We developed 27 fuzzy rules based on the literature and our domain knowledge, and we ran the fuzzy inference system for four of the proposed market-based measures. Finally, we evaluated our results and compared them with the IMO Expert Group study. Although not all measures responded the same, especially regarding the emission reductions, the percentage agreement is satisfactory in most of the cases (60–95%). The strength of the tool is that it synthesizes a large amount of information in a logical and transparent framework, and has the potential to have wider application in the context of market-based measures.

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