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. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Pardo, M. J., & De La Fuente, D. (2010). Uncertainty invariance transformation in continuous case. In Advances in Intelligent and Soft Computing (Vol. 77, pp. 491–498). Springer Verlag. https://doi.org/10.1007/978-3-642-14746-3_61
Mendeley helps you to discover research relevant for your work.