Summary
A concept of uncertain variables and their application in a class of uncertain systems has been developed. In this paper, after a short description of uncertain variables, nonparametric decision problems based on uncertain, random and fuzzy variables are presented. The analogies lead to the formulation of so called soft variables described by evaluating functions, introduced as a tool for a unification and generalization of decision problems based on uncertain knowledge representations. The application of the soft variables to a class of decision problems and a “principle of equivalency” concerning two different formulations of a knowledge given by an expert are presented.
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Bubnicki, Z. (2003). Soft Variables as a Generalization of Uncertain, Random and Fuzzy Variables. In: Rutkowski, L., Kacprzyk, J. (eds) Neural Networks and Soft Computing. Advances in Soft Computing, vol 19. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1902-1_2
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DOI: https://doi.org/10.1007/978-3-7908-1902-1_2
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-0005-0
Online ISBN: 978-3-7908-1902-1
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