Historically, the design of the in-stope pillar in underground excavations has been based on empirical formulae and numerical modelling. Although these design methods have been extensively applied in several gold mines in South Africa, rockburst, in-stope pillar burst/failure are continuously reported as the major problem faced by mines. Therefore, this study attempts to compare the performance...

1 Center for Research into Ecological and Environmental Modelling, School of Mathematics and Statistics, University of St Andrews, UK. 2 Boyd Orr Centre for Population and Ecosystem Health, College of Medical Veterinary and Life Sciences, University of Glasgow, UK. 3 School of Mathematics and Statistics, University of Sheffield, UK. 4 South African Environmental Observation Network, Fynbos Node...

Existing public domain enterprise engineering methodologies provide a backbone of modelling concepts designed to maintain consistency between common engineering concerns during different life phases of enterprise systems. The literature reports industrial examples of the use of such a backbone of modelling concepts to formally structure and support large-scale systems engineering. This has led ...

UML is posited as the “swiss army knife” for systems modelling and design activities. It embodies a number of modelling formalisms that have broad applicability in capturing both the static and dynamic aspects of software systems. One area of UML that has received particular attention is that of Activity Diagrams (ADs), which provide a high-level means of modelling dynamic system behaviour. In ...

Agent-based simulation (ABS) modelling had been a prevalent approach in simulating dynamic processes for a variety of domains. However, the constructed models are usually domain-specific in nature. The proprietary issue of existing modelling approaches limit the possibilities of reusing those constructed models in other application domains. Such limitation also poses issues in model extensibili...

The Gaussian-process (GP) model is an example of a probabilistic, nonparametric model with uncertainty predictions. It can be used for the modelling of complex nonlinear systems and also for dynamic systems identification. The output of the GP model is a normal distribution, expressed in terms of the mean and variance. At present it is applied mostly for the modelling of dynamic systems with on...

In this paper the continuous-time competing-risk approach to dynamic microsimulation modelling and approaches based on a discrete-time framework are compared in a systematic way. Besides the basic modelling approaches the possibilities to extend the models to include quantitative and qualitative dependent variables, to use macroeconomic explanatory variables, and to account for dependencies bet...