Dynamic calibration of agent based models using data assimilation

dc.contributor.author	Ward, Jonathan A.	en_US
dc.contributor.author	Evans, Andrew J.	en_US
dc.contributor.author	Malleson, Nicolas S.	en_US
dc.date.accessioned	2016-07-04T03:49:01Z
dc.date.available	2016-07-04T03:49:01Z
dc.date.issued	2016	en_US
dc.identifier.other	HPU4160368	en_US
dc.identifier.uri	https://lib.hpu.edu.vn/handle/123456789/21883	en_US
dc.description.abstract	A widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. First, we want to present the EnKF in a simple setting for the benefit of ABM practitioners who are unfamiliar with it.	en_US
dc.format.extent	17 p.	en_US
dc.format.mimetype	application/pdf	en_US
dc.language.iso	en	en_US
dc.subject	Mathematics	en_US
dc.subject	Data assimilation	en_US
dc.subject	Systems	en_US
dc.title	Dynamic calibration of agent based models using data assimilation	en_US
dc.type	Article	en_US
dc.size	2.87MB	en_US
dc.department	Education	en_US