Session
Computer Science and Communication Engineering
Description
In this work we present two structurally different mathematical models for the prognostic simulation of Austria’s population: A time-continuous, macroscopic system dynamics approach and a time-discrete, microscopic agent-based approach. Both models were developed as case studies of a series of population concepts in order to support models for decision-support in Austria’s health care system. In the present work we want to focus on the definition, the parametrisation as well as especially the validation process of both population-models. The latter was of special interest as it included a cross-model validation with Statistics Austria’s own prognostic model SIKURS.
Keywords:
population model, model comparison, validation, cross-model validation
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-550-14-7
First Page
174
Last Page
178
Location
Durres, Albania
Start Date
7-11-2015 9:00 AM
End Date
7-11-2015 5:00 PM
DOI
10.33107/ubt-ic.2015.107
Recommended Citation
Bicher, Martin; Glock, Barbara; Miksch, Florian; Popper, Niki; and Schneckenreither, Günter, "Definition, Validation and Comparison of Two Population Models for Austria" (2015). UBT International Conference. 107.
https://knowledgecenter.ubt-uni.net/conference/2015/all-events/107
Definition, Validation and Comparison of Two Population Models for Austria
Durres, Albania
In this work we present two structurally different mathematical models for the prognostic simulation of Austria’s population: A time-continuous, macroscopic system dynamics approach and a time-discrete, microscopic agent-based approach. Both models were developed as case studies of a series of population concepts in order to support models for decision-support in Austria’s health care system. In the present work we want to focus on the definition, the parametrisation as well as especially the validation process of both population-models. The latter was of special interest as it included a cross-model validation with Statistics Austria’s own prognostic model SIKURS.
