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Interdisciplinary Description of Complex Systems : INDECS, Vol.2 No.1 June 2004. -

The better the model, the more features of the problem it explains. However, showing that the model has similarities to that of a phenomena is often less significant in applications due to lack of data. Forecasting, as special application of modelling, is neither an exception: besides

statistical data one should use several types of subjective assumptions about the present and the future state of the model. In case of complex models, this fact is extremely important, because these models use often unobservable, hidden or – regarding its future evolution – uncertain

variables. We developed a simple mathematical approach how these uncertainties can be managed in the model. We shall also show how these uncertainties can influence the behaviour of modelled variables, and how an approximate for time horizon of forecasts can be calculated.

complex systems; futures studies; foresight; modelling; time horizon

Autor: Péter Alács - ; Futures Studies Centre, Budapest University of Economic Sciences and Public Administration



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