[1] viXra:1010.0039 [pdf] submitted on 25 Oct 2010
Authors: Xin-De Li, Xian-Zhong Dai, Jean Dezert, Florentin Smarandache
Comments: 340 pages
In this paper, we present a new 2-tuple linguistic
representation model, i.e. Distribution Function Model
(DFM), for combining imprecise qualitative information using
fusion rules drawn from Dezert-Smarandache Theory
(DSmT) framework. Such new approach allows to preserve
the precision and efficiency of the combination of linguistic
information in the case of either equidistant or unbalanced
label model. Some basic operators on imprecise 2-tuple labels
are presented together with their extensions for imprecise
2-tuple labels. We also give simple examples to show
how precise and imprecise qualitative information can be
combined for reasoning under uncertainty. It is concluded
that DSmT can deal efficiently with both precise and imprecise
quantitative and qualitative beliefs, which extends the
scope of this theory.
Category: Artificial Intelligence