Generating synthetic baseline populations from register data
Publication: Research - peer-review › Journal article – Annual report year: 2012
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Generating synthetic baseline populations from register data. / Rich, Jeppe; Mulalic, Ismir.
In: Transportation Research. Part A: Policy & Practice, Vol. 46, No. 3, 2012, p. 467-479.Publication: Research - peer-review › Journal article – Annual report year: 2012
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TY - JOUR
T1 - Generating synthetic baseline populations from register data
A1 - Rich,Jeppe
A1 - Mulalic,Ismir
AU - Rich,Jeppe
AU - Mulalic,Ismir
PB - Pergamon
PY - 2012
Y1 - 2012
N2 - The paper presents a population synthesiser based on the method of Iterative Proportional Fitting (IPF) algorithm developed for the new Danish national transport model system. The synthesiser is designed for large population matrices and allows target variables to be represented in several target constraints. As a result, constraints for the IPF are cross-linked, which makes it difficult to ensure consistency of targets in a forecast perspective. The paper proposes a new solution strategy to ensure internal consistency of the population targets in order to guarantee proper convergence of the IPF algorithm. The solution strategy consists in establishing a harmonisation process for the population targets, which combined with a linear programming approach, is applied to generate a consistent target representation. The model approach is implemented and tested on Danish administrative register data. A test on historical census data shows that a 2006 population could be predicted by a 1994 population with an overall percentage deviation of 5–6% given that targets were known. It is also indicated that the deviation is approximately a linear function of the length of the forecast period.
AB - The paper presents a population synthesiser based on the method of Iterative Proportional Fitting (IPF) algorithm developed for the new Danish national transport model system. The synthesiser is designed for large population matrices and allows target variables to be represented in several target constraints. As a result, constraints for the IPF are cross-linked, which makes it difficult to ensure consistency of targets in a forecast perspective. The paper proposes a new solution strategy to ensure internal consistency of the population targets in order to guarantee proper convergence of the IPF algorithm. The solution strategy consists in establishing a harmonisation process for the population targets, which combined with a linear programming approach, is applied to generate a consistent target representation. The model approach is implemented and tested on Danish administrative register data. A test on historical census data shows that a 2006 population could be predicted by a 1994 population with an overall percentage deviation of 5–6% given that targets were known. It is also indicated that the deviation is approximately a linear function of the length of the forecast period.
KW - Population synthesising
KW - Iterative Proportional Fitting (IPF)
KW - Transport demand modelling
KW - Model forecasting
U2 - 10.1016/j.tra.2011.11.002
DO - 10.1016/j.tra.2011.11.002
JO - Transportation Research. Part A: Policy & Practice
JF - Transportation Research. Part A: Policy & Practice
SN - 0965-8564
IS - 3
VL - 46
SP - 467
EP - 479
ER -