Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/20990
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dc.contributor.authorECTORS, Wim-
dc.contributor.authorKOCHAN, Bruno-
dc.contributor.authorKNAPEN, Luk-
dc.contributor.authorJANSSENS, Davy-
dc.contributor.authorBELLEMANS, Tom-
dc.date.accessioned2016-04-13T13:51:17Z-
dc.date.available2016-04-13T13:51:17Z-
dc.date.issued2016-
dc.identifier.citationProcedia Computer Science, p. 34-41-
dc.identifier.issn1877-0509-
dc.identifier.urihttp://hdl.handle.net/1942/20990-
dc.description.abstractMany activity-based models start by scheduling inflexible or mandatory activities (if present), before more flexible activities. Often work and educational activities are assumed as most stringent and recognized as the only mandatory activities. According to this definition, only 45% of all schedules contains a mandatory activity (OVG single-day travel survey in Flanders, Belgium). This means 55% of schedules does not have a traditional mandatory-flexible activity structure. This research proposes a completely data-driven approach to reveal the real basic structure of individuals’ schedules, i.e. the skeleton schedule sequence. To this end, a sequential clustering algorithm was developed. Furthermore, an in-depth analysis of the parameter settings was performed. The proposed method reveals a set of skeleton activity schedules and confirms the importance of work and education.-
dc.language.isoen-
dc.relation.ispartofseriesProcedia Computer Science-
dc.rights© 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).-
dc.subject.otherskeleton schedules; activity patterns; mandatory activities; activity-based modeling-
dc.titleA generic data-driven sequential clustering algorithm determining activity skeletons-
dc.typeProceedings Paper-
local.bibliographicCitation.conferencedate23-26 May 2016-
local.bibliographicCitation.conferencenameThe 7th International Conference on Ambient Systems, Networks and Technologies (ANT 2016)-
local.bibliographicCitation.conferenceplaceMadrid, Spain-
dc.identifier.epage41-
dc.identifier.spage34-
local.bibliographicCitation.jcatC1-
dc.description.notesEctors, W (reprint author), Hasselt Univ, Transportat Res Inst, Wetenschapspk 5 Box 6, B-3590 Diepenbeek, Belgium. wim.ectors@uhasselt.be-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
local.relation.ispartofseriesnr83-
dc.identifier.doi10.1016/j.procs.2016.04.096-
dc.identifier.isi000387655000004-
local.bibliographicCitation.btitleProcedia Computer Science-
item.fulltextWith Fulltext-
item.fullcitationECTORS, Wim; KOCHAN, Bruno; KNAPEN, Luk; JANSSENS, Davy & BELLEMANS, Tom (2016) A generic data-driven sequential clustering algorithm determining activity skeletons. In: Procedia Computer Science, p. 34-41.-
item.accessRightsOpen Access-
item.validationecoom 2017-
item.contributorECTORS, Wim-
item.contributorKOCHAN, Bruno-
item.contributorKNAPEN, Luk-
item.contributorJANSSENS, Davy-
item.contributorBELLEMANS, Tom-
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