Aspects of Uncertainty in Qualitative Systems Modeling

  • George J. Klir
Part of the Advances in Simulation book series (ADVS.SIMULATION, volume 5)


It is argued in this chapter that uncertainty is a valuable commodity in systems modeling, which can be traded for a reduction of complexity or an increase of credibility of systems models. Principles of maximum and minimum uncertainty are introduced as fundamental to problems involving ampliative reasoning and problems of systems simplification, respectively. Novel mathematical theories for dealing with uncertainty and measures of relevant types of uncertainty in these theories are overviewed. It is shown that uncertainty is a multidimensional concept, and consequently, the principles of maximum and minimum uncertainty must be formulated as multiple objective criteria optimization problems.


Shannon Entropy Fuzzy Measure Inductive Modeling Maximum Entropy Principle Focal Element 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag New York, Inc. 1991

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  • George J. Klir

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