Possibility theory was initiated by Zadeh in 1978 as an alternative to probability theory. Probability theory is not efficient in the study of those uncertainty situations in which phenomena occur with a small frequency. In such cases it is preferable to apply techniques offered by possibility theory.In foundation of possibility theory one started on a paralel line with probability theory. Rand...

In this technical report, the systematic investigation of lattice-valued possibilistic measures, opened in the first part of this report (cf. Technical Report No. 952, ICS AS CR, December 2005) is pursued and focused towards possibilistic variants of the notions of outer (upper) and lower (inner) possibilistic measures induced by a given partial possibilistic measure. The notion of Lebesgue mea...

Dubois and Prade introduced the mean value of a fuzzy number as a closed interval bounded by the expectations calculated from its upper and lower distribution functions. In this paper introducing the notations of lower possibilistic and upper possibilistic mean values we definine the interval-valued possibilistic mean and investigate its relationship to the interval-valued probabilistic mean. W...

In this paper we define the semantics for capturing possibilistic ordered disjunction programs based on pstable semantics. The pstable semantics, based on paraconsistent logic, allows to treat inconsistency programs. Moreover being closer to possibilistic inference it allows to extend the necessity-values of the clauses to be considered, causing a higher level of comparison at the moment of sel...

In medical imaging uncertainty is widely present in data, because of the noise in acquisition and of the partial volume effects originating from the low resolution of sensors. In particular, borders between tissues are not exactly defined and memberships in the boundary regions are intrinsically fuzzy. Therefore, computer assisted unsupervised fuzzy clustering methods turn out to be particularl...

Fuzzy c-means (FCM) clustering is based on minimizing the fuzzy within cluster scatter matrix trace but FCM neglects the between cluster scatter matrix trace that controls the distances between the class centroids. Based on the principle of cluster centers separation, fuzzy cluster centers separation (FCCS) clustering is an extended fuzzy c-means (FCM) clustering algorithm. FCCS attaches import...

Magnetic resonance imaging is often the medical imaging method of choice when soft-tissue delineation is necessary. This paper presents a new approach for automated detection of brain tumor based on k-means and possibilistic c-means clustering with color segmentation, which separates brain tumor from healthy tissues in magnetic resonance images. The magnetic resonance feature images used for th...

Based on our earlier work on partial logics and extended logic programs Wag91, Wag94, HJW96], and on the possibilistic logic of DLP94], we deene a compositional possibilistic rst-order logic with two kinds of negation as the logical basis of semi-possibilistic and possibilis-tic logic programs. We show that in the same way as the minimal model semantics of relational databases can be reened to ...

This paper uses the concept of possibilistic risk aversion to propose a new approach for portfolio selection in fuzzy environment. Using possibility theory, the possibilistic mean, variance, standard deviation and risk premium of a fuzzy number are established. Possibilistic Sharpe ratio is defined as the ratio of possibilistic risk premium and possibilistic standard deviation of a portfolio. T...