Modeling of Ship Propulsion Performance

Benjamin Pjedsted Pedersen, Jan Larsen

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


    Full scale measurements of the propulsion power, ship speed, wind speed and direction, sea and air temperature, from four different loading conditions has been used to train a neural network for prediction of propulsion power. The network was able to predict the propulsion power with accuracy between 0.8-2.8%, which is about the same accuracy as for the measurements. The methods developed are intended to support the performance monitoring system SeaTrend® developed by FORCE Technology (FORCE (2008)).
    Original languageEnglish
    Title of host publicationWorld Maritime Technology Conference
    VolumeSession 4A
    Publication date2009
    Publication statusPublished - 2009
    EventModeling of Ship Propulsion Performance -
    Duration: 1 Jan 2009 → …


    ConferenceModeling of Ship Propulsion Performance
    Period01/01/2009 → …


    • propulsion
    • ship
    • performance
    • maritime
    • Neural network


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