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dc.contributor.authorBobek, S
dc.contributor.authorTadeja, Slawomir
dc.contributor.authorStruski, Ł
dc.contributor.authorStachura, P
dc.contributor.authorKipouros, Timoleon
dc.contributor.authorTabor, J
dc.contributor.authorNalepa, GJ
dc.contributor.authorKristensson, Per Ola
dc.date.accessioned2022-01-11T00:30:06Z
dc.date.available2022-01-11T00:30:06Z
dc.date.issued2021-12-30
dc.identifier.issn1454-5101
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/332580
dc.description.abstract<jats:p>We present a refinement of the Immersive Parallel Coordinates Plots (IPCP) system for Virtual Reality (VR). The evolved system provides data-science analytics built around a well-known method for visualization of multidimensional datasets in VR. The data-science analytics enhancements consist of importance analysis and a number of clustering algorithms including a novel SuMC (Subspace Memory Clustering) solution. These analytical methods were applied to both the main visualizations and supporting cross-dimensional scatter plots. They automate part of the analytical work that in the previous version of IPCP had to be done by an expert. We test the refined system with two sample datasets that represent the optimum solutions of two different multi-objective optimization studies in turbomachinery. The first one describes 54 data items with 29 dimensions (DS1), and the second 166 data items with 39 dimensions (DS2). We include the details of these methods as well as the reasoning behind selecting some methods over others.</jats:p>
dc.publisherMDPI AG
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleVirtual reality-based parallel coordinates plots enhanced with explainable ai and data-science analytics for decision-making processes
dc.typeArticle
dc.publisher.departmentDepartment of Engineering
dc.date.updated2022-01-05T07:40:02Z
prism.endingPage331
prism.issueIdentifier1
prism.publicationDate2021
prism.publicationNameApplied Sciences (Switzerland)
prism.startingPage331
prism.volume12
dc.identifier.doi10.17863/CAM.79756
dcterms.dateAccepted2021-12-25
rioxxterms.versionofrecord10.3390/app12010331
rioxxterms.versionVoR
dc.contributor.orcidTadeja, Slawomir [0000-0003-0455-4062]
dc.contributor.orcidKipouros, Timoleon [0000-0003-3392-283X]
dc.contributor.orcidKristensson, Per Ola [0000-0002-7139-871X]
dc.identifier.eissn2076-3417
rioxxterms.typeJournal Article/Review
pubs.funder-project-idEPSRC (1788814)
cam.issuedOnline2021-12-30
cam.depositDate2022-01-05
pubs.licence-identifierapollo-deposit-licence-2-1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International