Uncertainty qualification in simulations

Basit Öğe Kaydı
dc.contributor.authorHussaini, M. Y.
dc.date.accessioned2024-07-12T20:52:10Z
dc.date.available2024-07-12T20:52:10Z
dc.date.issued2009en_US
dc.departmentFakülteler, İnsan ve Toplum Bilimleri Fakültesi, Matematik Bölümüen_US
dc.description.abstractUncertainty in simulations is due to the stochastic nature of geometric and physical parameters, the indeterminate nature of initial/boundary conditions, and the inadequacy of physical models coupled with discretization errors. These uncertainties can be classi¯ed into two types: parametric (aleatory) and model form (epistemic). Whereas probability theory can deal with parametric uncertainty, some generalization of probability theory is required to deal with the model form of uncertainty. Among the generalizations of probability theory, evidence theory is relatively well-developed. The presentation will briefly discuss some techniques based on these theories to quantify uncertainty in the context of some representative problems.en_US
dc.identifier.citationHussaini, M. Y. (2009). Uncertainty qualification in simulations. International Conference on Mathematical Sciences, Maltepe Üniversitesi. s. 26-27.en_US
dc.identifier.endpage27en_US
dc.identifier.isbn9.78605E+12
dc.identifier.startpage26en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12415/2532
dc.institutionauthorHussaini, M. Y.
dc.language.isoenen_US
dc.publisherMaltepe Üniversitesien_US
dc.relation.ispartofInternational Conference on Mathematical Sciencesen_US
dc.relation.publicationcategoryUluslararası Konferans Öğesi - Başka Kurum Yazarıen_US
dc.rightsCC0 1.0 Universal*
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.snmzKY07916
dc.titleUncertainty qualification in simulationsen_US
dc.typeConference Object
dspace.entity.typePublication

Dosyalar

Koleksiyon

İnsan ve Toplum Bilimleri Fakültesi Koleksiyonu