Uncertainty Invariance Transformation in Continuous Case

In this work, a general procedure for transforming a possibility distribution into a probability density function, in the continuous case, is proposed, in a way that the resulting distribution contains the same uncertainty as the original distribution. A significant aspect of this approach is that it makes use of Uncertainty Invariance Principle which is itself a general procedure for going from an initial representation of uncertainty to a new representation.

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