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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/2050

Title: The impact of simplification in a sequential rule-based model of activity-scheduling behavior
Authors: MOONS, Elke
WETS, Geert
Arentze, Theo A.
Issue Date: 2005
Publisher: PION LTD
Citation: ENVIRONMENT AND PLANNING A, 37(3). p. 551-568
Abstract: The aim of this paper is to gain a better understanding of the impact of simplification on a sequential model of activity-scheduling behavior which uses feature-selection methods. To that effect, the predictive performance of the Albatross model, which incorporates nine different facets of activity-travel behavior, based on the original full decision trees, is compared with the performance of the model based on trimmed decision trees. The results indicate that significantly smaller decision trees can be used for modeling the different choice facets of the sequential model system without losing much in predictive power. The performance of the models is compared at three levels: the choice-facet level, the activity-pattern level (comparing the observed and generated sequences of activities), and the trip-matrix level, comparing the correlation coefficients that determine the strength of the associations between the observed and the predicted origin-destination matrices. The results indicate that the model based on the trimmed decision trees predicts activity-diary schedules with a minimum loss of accuracy at the decision level. Moreover, the results indicate a slightly better performance at the activity-pattern and the trip-matrix level.
Notes: Limburgs Univ Ctr, Data Anal & Modeling Grp, B-3590 Diepenbeek, Belgium. Limburgs Univ Ctr, Ctr Stat, B-3590 Diepenbeek, Belgium. Eindhoven Univ Technol, Urban Planning Grp, NL-5600 MB Eindhoven, Netherlands.Moons, EALMG, Limburgs Univ Ctr, Data Anal & Modeling Grp, Univ Campus, B-3590 Diepenbeek, Belgium.elke.moons@luc.ac.be geert.wets@luc.ac.be marc.aerts@luc.ac.be t.a.arentze@bwk.tue.nl h.j.p.timmermans@bwk.tue.nl
URI: http://hdl.handle.net/1942/2050
DOI: 10.1068/a36167
ISI #: 000227946800011
ISSN: 0308-518X
Category: A1
Type: Journal Contribution
Validation: ecoom, 2006
Appears in Collections: Research publications

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