Abstract
A model is a simplified representation of the physical system. They are the tools to simulate the behaviour of physical systems. They can predict the future evolution of the systems, they can be used as interpretative tools in order to study system dynamics, and they can give hints for data collection and design of experiments (Giudici 2002).
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Notes
- 1.
Systems that show surprising and unanticipated or ‘emergent’ behaviours as shown in patterns that arise at the aggregate level from the operation of system processes at the micro or agent level. Such systems are intrinsically unpredictable in an overall sense but can be fashioned in such a way that makes knowledge of them useful and certain. Cities are the archetypical example, but so too is the economy. (Batty 2009).
- 2.
This concept assumes that everything which exists is no more extensive than its physical properties; this concept means that there are no kinds of things other than physical things.
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Model calibration is to determine the numerical values of model parameters, given some data set. A calibrated model is often believed to be a tool ready to forecast a system’s behaviour.
- 4.
Model validation assesses the model’s ability to predict the behaviour of the system under conditions different from those used in the calibration phase. This is usually done by comparing the model forecasts and the observations for a time period following that for which the model was originally calibrated.
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Bhatta, B. (2010). Modelling and Simulation of Urban Growth. In: Analysis of Urban Growth and Sprawl from Remote Sensing Data. Advances in Geographic Information Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05299-6_7
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DOI: https://doi.org/10.1007/978-3-642-05299-6_7
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