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