Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/20990
Title: A generic data-driven sequential clustering algorithm determining activity skeletons
Authors: ECTORS, Wim 
KOCHAN, Bruno 
KNAPEN, Luk 
JANSSENS, Davy 
BELLEMANS, Tom 
Issue Date: 2016
Source: Procedia Computer Science, p. 34-41
Series/Report: Procedia Computer Science
Series/Report no.: 83
Abstract: Many 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.
Notes: Ectors, W (reprint author), Hasselt Univ, Transportat Res Inst, Wetenschapspk 5 Box 6, B-3590 Diepenbeek, Belgium. wim.ectors@uhasselt.be
Keywords: skeleton schedules; activity patterns; mandatory activities; activity-based modeling
Document URI: http://hdl.handle.net/1942/20990
DOI: 10.1016/j.procs.2016.04.096
ISI #: 000387655000004
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/).
Category: C1
Type: Proceedings Paper
Validations: ecoom 2017
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
1-s2.0-S1877050916301193-main.pdfPublished version187.22 kBAdobe PDFView/Open
Show full item record

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.