A Convolutional Neural Network Developed to Predict Speed Using Operational Data

S.R.A. de Geus-Moussault, Mark Buis, H.J. Koelman

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

84 Downloads (Pure)

Abstract

In the shipping industry power prediction methods are commonly used. An option is to predict the power based with a theoretical analysis. However, with a purely theoretical approach it is not possible to evaluate all operating conditions. The second, simulation methods, are able to describe all the necessary quantities in detail. Nonetheless, simulation requires relatively high computational power. Thus, the current power prediction methods used in the shipping industry are insufficiently all-encompassing or accessible. Therefore, a machine learning approach is developed to calculate the ships speed over ground using neural network and convolutional neural network techniques. For training and validation of the model operational data from a fall-pipe vessel is used. The developed method combined with ship motion could result in an optimal power usage, and thus leads to reduced fuel consumption and emissions. The method could also be used for optimised routing. Although in this case study applied to one single vessel, the developed model is generally applicable, providing ship management companies the possibility to train the model with operational data from their fleet, therewith, offering the possibility of reduced fuel consumption and thus emissions on a global level.
Original languageEnglish
Title of host publicationProceedings of the 20th International Conference on Computer and IT Applications in the Maritime Industries, COMPIT’21
EditorsVolker Bertram
PublisherTechnische Universität Hamburg-Harburg
Pages246-264
ISBN (Print)978-3-89220-724-5
Publication statusPublished - 2021
EventCOMPIT ’21: 20th International Conference on Computer and IT Applications in the Maritime Industries - Mülheim, Germany
Duration: 9 Aug 202110 Aug 2021

Conference

ConferenceCOMPIT ’21: 20th International Conference on Computer and IT Applications in the Maritime Industries
Country/TerritoryGermany
CityMülheim
Period9/08/2110/08/21

Fingerprint

Dive into the research topics of 'A Convolutional Neural Network Developed to Predict Speed Using Operational Data'. Together they form a unique fingerprint.

Cite this