Abstract
As a matter of fact in many real situations uncertainty is not only present in form of randomness (stochastic uncertainty) but also in form of fuzziness (imprecision), for instance due to the inexactness of measurements of continuous quantities. From the probabilistic point of view the unavoidable fuzziness of measurements has (amongst others) the following far-reaching consequence: According to the classical Strong Law of Large Numbers (SLLN), the probability of an event B can be regarded as the limit of the relative frequencies of B induced by a sequence of identically distributed, independent, integrable random variables (X n )nāā (with probability one).
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Trutschnig, W. (2006). Fuzzy Probability Distributions Induced by Fuzzy Random Vectors. In: Lawry, J., et al. Soft Methods for Integrated Uncertainty Modelling. Advances in Soft Computing, vol 37. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-34777-1_10
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DOI: https://doi.org/10.1007/3-540-34777-1_10
Publisher Name: Springer, Berlin, Heidelberg
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