COMPLEXITY AND UNCERTAINTY IN THE FORECASTING OF COMPLEX SOCIAL SYSTEMS

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 da...

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Bibliographic Details
Main Author: Peter Alacs
Format: Article
Language:English
Published: Croatian Interdisciplinary Society 2004-06-01
Series:Interdisciplinary Description of Complex Systems
Subjects:
Online Access:http://indecs.eu/2004/indecs2004-pp88-94.pdf
Description
Summary: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.
ISSN:1334-4684
1334-4676