Simulation and Discrete-Event Modelling

A future task to be undertaken would be the inclusion of uncertainty in automatically produced models, for situations where accurate information cannot be provided for the model. This would require provision of a way of handling uncertainty for parameters within the ontology, e.g. as 3 values describing a triangular distribution rather than a unique absolute value. The decision support meta-program could be expanded to write out the code to run Monte-Carlo sampling, hence making use of the statistical uncertainty capability. Miller and Baramidze (2005) examine efforts to develop mathematical semantic representations above the syntactical representations of MathML. this effort should make it possible for standardisation of the representation of mathematical expressions that relate nodes, and their values and expressions, to each other. The next stage in the research surrounding this thesis will be provision of constraints to prevent invalid mathematical expressions. Miller and Baramidze also explain their research in Discrete-Event Modelling Ontology (DeMO) for simulation and modelling. This uses OWL to define a simulation and modelling class hierarchy. It would be very useful to create an example to demonstrate this with a practical model to test the use of this ontology.

References

MathML - http://www.w3.org/Math/.

Miller, J. A., Baramidze, G., 2005. Simulation and the Semantic Web. In. Proceedings of the 2005 Winter Simulation Conference. - http://www.informs-cs.org/wsc05papers/297.pdf.

More Information is available at -

Modelling - http://www.cems.uwe.ac.uk/amrc/seeds/Modelling.htm.

Semantic Web Modelling - http://www.cems.uwe.ac.uk/amrc/seeds/ModellingSemanticWeb.htm.