Complex real-life structures and systems can often be represented in a mathematical or statistical way. They can be conceptual models to better understand or simplify a process, or detailed data driven mathematical models to provide a theoretical understanding of relationships in a quantifiable way. Importantly, they need to be built so that the main characteristics are captured while simplifying the superfluous.
Developing a suitable model is the key. Once the model has been developed, simulations of the real-life system can be built in an artificial environment enabling a wide range of scenarios to be tested by changing the influential factors and observing the outputs under various conditions. Some simulations are deterministic, while some involve random aspects. Data Analysis Australia can then use the models for:
- Understanding the inter-relationships of components in the system;
- Sensitivity analysis to determine factors that most influence outputs;
- Predicting the long-term behaviour of the system;
- Predicting how the system responds when changes are made to the factors influencing it; and
- Optimising the system without the risks of upsetting the real operations.