Modelling of a stochastic continuous system

dc.contributor.authorAlbertyn, Martin
dc.contributor.authorKruger, P.S. (Paul Stephanus), 1944-
dc.date.accessioned2012-11-26T08:39:09Z
dc.date.available2012-11-26T08:39:09Z
dc.date.issued1998
dc.descriptionPresented at the 11th European Simulation Multiconference (ESM'97) in Istanbul. Turkey (1-4 June 1997) and included in the conference proceedings.en_US
dc.description.abstractThe key objective is to develop a method which can be utilized to model a stochastic continuous system. A system from the "real world" is used as the basis for the simulation modelling technique that is presented. The conceptualization phase indicates that the model has to incorporate stochastic and deterministic elements. A method is developed that utilizes the discrete simulation ability of a stochastic package (ARENA), in conjunction with a deterministic package (FORTRAN), to model the continuous system. (Software packages tend to specialize in either stochastic, or deterministic modelling.) The length of the iteration time interval and adequate sample size are investigated. The method is authenticated by the verification and validation ofthe defined model. Two scenarios are modelled and the results are discussed . Conclusions are presented and strengths and weaknesses of this method are considered and discussed .en_US
dc.description.urihttp://sajie.journals.ac.zaen_US
dc.format.extent9 pagesen_US
dc.format.mediumPDFen_US
dc.identifier.citationAlbertyn, M & Kruger, PS 1998, 'Modelling of a stochastic continuous system', The South African Journal of Industrial Engineering, vol. 9, no. 1, pp. 1-9.en_US
dc.identifier.issn1012-277X (print)
dc.identifier.issn2224-7890 (on-line)
dc.identifier.urihttp://hdl.handle.net/2263/20485
dc.language.isoenen_US
dc.publisherSouthern African Institute for Industrial Engineeringen_US
dc.rightsSouthern African Institute for Industrial Engineeringen_US
dc.subjectSimulation modelen_US
dc.subjectContinuous modelen_US
dc.subjectStochastic modelen_US
dc.subjectDeterministic modelen_US
dc.subjectContinuous process planten_US
dc.titleModelling of a stochastic continuous systemen_US
dc.typeArticleen_US

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