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dc.contributor.authorWalker, DJ
dc.contributor.authorCraven, MJ
dc.date.accessioned2018-04-18T11:59:26Z
dc.date.issued2018-03-08
dc.description.abstractA visualisation method is presented that is intended to assist evolutionary algorithm users with the parametrisation of their algorithms. The visualisation method presents the convergence and diversity properties such that different parametrisations can be easily compared, and poor performing parameter sets can be easily identified and discarded. The efficacy of the visualisation is presented using a set of benchmark optimisation problems from the literature, as well as a benchmark water distribution network design problem. Results show that it is possible to observe the different performance caused by different parametrisations. Future work discusses the potential of this visualisation within an online tool that will enable a user to discard poor parametrisations as they execute to free up resources for better ones.en_GB
dc.identifier.citationVol. 10784, pp. 547 - 560en_GB
dc.identifier.doi10.1007/978-3-319-77538-8_38
dc.identifier.urihttp://hdl.handle.net/10871/32489
dc.language.isoenen_GB
dc.publisherSpringer Verlagen_GB
dc.rights© Springer International Publishing AG, part of Springer Nature 2018.en_GB
dc.subjectVisualisationen_GB
dc.subjectMulti-objectiveen_GB
dc.subjectOptimisationen_GB
dc.subjectWater Distribution Network Designen_GB
dc.titleToward the Online Visualisation of Algorithm Performance for Parameter Selectionen_GB
dc.typeArticleen_GB
dc.date.available2018-04-18T11:59:26Z
dc.identifier.isbn9783319775371
dc.identifier.issn0302-9743
dc.descriptionThis is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this recorden_GB
dc.identifier.journalSim K., Kaufmann P. (eds) Applications of Evolutionary Computation. EvoApplications 2018. Lecture Notes in Computer Scienceen_GB


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