The 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 .
Presented at the 11th European Simulation Multiconference (ESM'97) in Istanbul. Turkey (1-4 June 1997) and included in the conference proceedings.
Since the emergence of systematic science it has been recognized that a natural phenomenon can be described
by different models that vary in their complexity and their ability to capture the details of the features
Terblanche, S.E. (Stephanus Esaias), 1940-; Stevens, Joseph Benjamin; Sekgota, Mpolaeng Gilbert(South African Society for Agricultural Extension, Department of Agriculture, Economics, Extension and Rural Development, University of Pretoria, 2014)
The Sustainable Restitution Support – South Africa (SRS-SA) program aimed at the development of a post-settlement support model that could be used to support beneficiaries of land reform in South Africa, especially those ...
Olivier, Laurentz Eugene; Craig, Ian K.(Elsevier, 2013-02)
The performance of a model predictive controller depends on the quality of
the plant model that is available. Often parameters in a run-of-mine (ROM)
ore milling circuit are uncertain and inaccurate parameter estimation ...