Zobrazit minimální záznam



dc.contributor.authorKukal J.
dc.contributor.authorTran Q.
dc.contributor.authorBeneš M.
dc.date.accessioned2020-03-08T21:11:55Z
dc.date.available2020-03-08T21:11:55Z
dc.date.issued2019
dc.identifierV3S-333212
dc.identifier.citationKUKAL, J., Q. TRAN, and M. BENEŠ. Discovery of rare event testing for stochastic simulations of diffusion processes. Physica A: Statistical Mechanics and Its Applications. 2019, 525(1), 50-63. ISSN 0378-4371. DOI 10.1016/j.physa.2019.03.020.
dc.identifier.issn0378-4371 (print)
dc.identifier.issn1873-2119 (online)
dc.identifier.urihttp://hdl.handle.net/10467/86996
dc.description.abstractStochastic modeling of diffusion processes in various spatial domains and with boundary conditions is widely applicable especially in combination with non-linear kinetics of chemical reactions. However, the comparison with exact solution is possible in simple cases e.g. linear diffusion models. The novel testing method introduced in this article enables to study the behavior of linear stochastic diffusion models with possible low particle concentration in target sub-domains. The proposed method is demonstrated on various diffusion models with the known Green function. The novel method is recommended whenever the chi(2) goodness-of-fit test fails or the localization of critical domains is required.eng
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofPhysica A: Statistical Mechanics and Its Applications
dc.subjectdiffusioneng
dc.subjectsimulationeng
dc.subjectrare eventseng
dc.subjectstatistical testingeng
dc.subjectGreen functioneng
dc.titleDiscovery of rare event testing for stochastic simulations of diffusion processeseng
dc.typečlánek v časopisecze
dc.typejournal articleeng
dc.identifier.doi10.1016/j.physa.2019.03.020
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/OPVVV/CZ.02.1.01%2F0.0%2F0.0%2F16_019%2F0000765/CZ/Research Center for Informatics/-
dc.rights.accessclosedAccess
dc.identifier.wos000474503900005
dc.type.statusPeer-reviewed
dc.type.versionpublishedVersion
dc.identifier.scopus2-s2.0-85063606692


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Zobrazit minimální záznam