A cover technique to verify the reliability of a model for calculating fuzzy probabilities

Many models have been suggested to calculate fuzzy probabilities in risk analysis. In general, the reliability of a model is demonstrated by practical effects or proved theoretically. In this article we suggest a new approach called the cover technique to verify the model’s reliability. The technique is based on a hypothesis that a statistical result can approximately confirm a fuzzy probability as a fuzzy-set-valued probability. A cover is constructed by many biprobability distributions. The consistency degree of a cover and a fuzzy probability distribution is employed to verify the reliability of a model. We present a case that shows how to construct a distribution-cover and calculate the consistency degree of the cover and a possibility-probability distribution. A series of numerical experiments with random samples from a normal distribution verify the reliability of the interior-outer-set model.

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