TY - GEN
T1 - Data Assimilation in Discrete Event Simulations: A Rollback Based Sequential Monte Carlo Approach
AU - Xie, Xu
AU - Verbraeck, Alexander
AU - Gu, Feng
N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
PY - 2016
Y1 - 2016
N2 - Data assimilation is an analysis technique which aims to incorporate measured observations into a dynamic system model in order to produce accurate estimates of the current state variables of the system. Although data assimilation is conventionally applied in continuous system models, it is also a desired ability for its discrete event counterpart. However, data assimilation has not been well studied in discrete event simulations yet. This paper researches data assimilation problems in discrete event simulations, and proposes a rollback based implementation of the Sequential Monte Carlo (SMC) method – the rollback based SMC method. To evaluate the accuracy of the proposed method, an identical-twin experiment in a discrete event traffic case is carried out and the results are presented and analyzed.
AB - Data assimilation is an analysis technique which aims to incorporate measured observations into a dynamic system model in order to produce accurate estimates of the current state variables of the system. Although data assimilation is conventionally applied in continuous system models, it is also a desired ability for its discrete event counterpart. However, data assimilation has not been well studied in discrete event simulations yet. This paper researches data assimilation problems in discrete event simulations, and proposes a rollback based implementation of the Sequential Monte Carlo (SMC) method – the rollback based SMC method. To evaluate the accuracy of the proposed method, an identical-twin experiment in a discrete event traffic case is carried out and the results are presented and analyzed.
KW - Data Assimilation
KW - Discrete event simulations
KW - Sequential Monte Carlo methods
KW - Rollback
UR - http://dl.acm.org/citation.cfm?id=2975389.2975400
U2 - 10.23919/TMS.2016.7918817
DO - 10.23919/TMS.2016.7918817
M3 - Conference contribution
SN - 978-1-5108-2321-1
T3 - TMS-DEVS '16
SP - 11:1-11:8
BT - Proceedings of the Symposium on Theory of Modeling Simulation (TMS-DEVS)
PB - Society for Computer Simulation International (SCS)
CY - San Diego, CA, USA
T2 - SpringSim-TMS/DEVS 2016
Y2 - 3 April 2016 through 6 April 2016
ER -