P(Z) logic offers a new way to reason about vagueness (ie fuzziness), that treats fuzziness as degrees, distinct from probabilities. One then applies probability distributions over fuzziness. This approach is different from both classical fuzzy logic [26] and possibility theory [1]. P(Z) logic is specially designed for common-sense reasoning.

Due to the complexities of objects and the vagueness of the human mind, it has attracted considerable attention from researchers studying fuzzy classification algorithms. In this paper, we propose a concept of fuzzy relative entropy to measure the divergence between two fuzzy sets. Applying fuzzy relative entropy, we prove the conclusion that patterns with high fuzziness are close to the classi...

in applications there occur different forms of uncertainty. the twomost important types are randomness (stochastic variability) and imprecision(fuzziness). in modelling, the dominating concept to describe uncertainty isusing stochastic models which are based on probability. however, fuzzinessis not stochastic in nature and therefore it is not considered in probabilisticmodels.since many years t...