Understanding wayfinding: A Bayesian network approach

Farr, Anna C. (2016) Understanding wayfinding: A Bayesian network approach. PhD by Publication, Queensland University of Technology.

Abstract

This research used statistical modelling to investigate the factors that contribute to how we find our way in transportation hubs, in particular, airports. Using Bayesian Networks, the researcher built a model that incorporated both the human and environmental factors required for effective wayfinding. This research has advanced the literature on how expert opinions can be combined in as well as contributing to improvement of the understanding of wayfinding in transportation hubs.

Impact and interest:

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Full-text downloads:

18 since deposited on 20 Sep 2016
18 in the past twelve months

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ID Code: 95789
Item Type: QUT Thesis (PhD by Publication)
Supervisor: Mengersen, Kerrie & Yarlagadda, Prasad
Keywords: Bayesian Networks, wayfinding, airports, visualisations, dashboards, expert elicitation, linear pooling, measurement error, expert opinion, measurement error models
Divisions: Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Institution: Queensland University of Technology
Deposited On: 20 Sep 2016 05:29
Last Modified: 20 Sep 2016 05:29

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