Predicting parking lot occupancy using Prediction Instrument Development for Complex Domains

Lijbers, J.M. (2016) Predicting parking lot occupancy using Prediction Instrument Development for Complex Domains.

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Abstract:In predictive analytics, complex domains are domains in which behavioural, cultural, political, and other soft factors, affect prediction outcome. A soft-inclusive domain analysis can be performed, to capture the effects of these (domain specific) soft factors. This research assesses the use of a soft-inclusive domain analysis, to develop a prediction instrument in a complex domain, versus the use of an analysis in which no soft factors are taken into account: a soft-exclusive analysis. A case study of predicting parking lot occupancy is used to test the methods. Results show no significant difference in predictive performance, when comparing the developed prediction instruments. Possible explanations for this result are: high predictive performance of the soft-exclusive developed predictive model, and the fact that not all soft factors, identified using softinclusive analysis, could be used in training the predictive model.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Business Information Technology MSc (60025)
Link to this item:http://purl.utwente.nl/essays/70713
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