In this article, we introduce a general concept of fuzzy operators. These operators are then used to generalize the possibilistic conditioning formulation proposed by Nguyen [1]. This generalization depends on the relation which exists between this conditioning and the probabilistic t-norm. By using other t-norms, other conditionings are obtained, and their properties are studied. One applicati...

In this paper, fuzzy quantitative models of language statistics are constructed. All suggested models are based on the assumption about a superposition of two kinds of uncertainties: probabilistic and possibilistic. The realization of this superposition in statistical distributions is achieved by the probability measure splitting procedure. In this way, the fuzzy versions of generalized binomia...

Statistical distribution of language structures reflect important regularities controlling informational and psycho-physiological processes, which accompany the generation of verbal language or printed texts. In this paper, fuzzy quantitative models of language statistics are constructed. The suggested models are based on the assumption about a super-position of two kinds of uncertainties: prob...

Construction of Fuzzy Control Charts Based on Weighted Possibilistic Mean Dabuxilatu Wang, Pinghui Li & Masami Yasuda a School of Economics and Statistics, Guangzhou University, Guangzhou, China b Research Center of Statistical Science Lingnan, Guangzhou University, Guangzhou, China c Faculty of Science, Chiba University, Chiba, Japan Accepted author version posted online: 16 Apr 2014.Published...

Contextuality and nonlocality are nonclassical properties exhibited by quantum statistics whose implications profoundly impact both the foundations applications of theory. In this paper we provide some insights into logical contextuality inequality-free proofs. The former can be understood as possibility version contextuality, while latter refers to proofs that not based on violations noncontex...

In this paper, we develop fuzzy, possibilistic hypothesis tests for testing crisp hypotheses a distribution parameter from data. these tests, fuzzy statistics are used, which produced by the possibility of estimated parameter, constructed known confidence intervals. The results in much better agreement with than ones respective popular book on statistics, uses critical values. We also present a...

This paper describes a new kind of language models based on the Possibility Theory. The purpose of these new models is to better use the data available on the Web for language modeling. These models aim to integrate information relative to impossible word sequences. We address the two main problems of using this kind of model: how to estimate the measures for word sequences and how to integrate...

We introduce the class of possibilistic nested logic programs. These possibilistic logic programs allow us to use nested expressions in the bodies and the heads of their rules. By considering a possibilistic nested logic program as a possibilistic theory, a construction of a possibilistic logic programing semantics based on answer sets for nested logic programs and the proof theory of possibili...

Possibilistic logic provides a convenient tool for dealing with inconsistency and handling uncertainty. In this paper, we propose possibilistic description logics as an extension of description logics. We give semantics and syntax of possibilistic description logics. We then define two inference services in possibilistic description logics. Since possibilistic inference suffers from the drownin...

Possibilistic networks and possibilistic logic bases are important tools to deal with uncertain pieces of information. Both of them offer a compact representation of possibility distributions. This paper studies a new representation format, called hybrid possibilistic networks, which cover both standard possibilistic networks and possibilistic knowledge bases. An adaptation of propagation algor...