Fuzzy Evidence in Bayesian Network

Author

Ben Mrad, Ali ; Maalej, Mohamed Amine ; Delcroix, Veronique ; Piechowiak, Sylvain ; Abid, Mohamed

Author_Institution

ENIS, Univ. of Sfax, Sfax, Tunisia

fYear

2011

fDate

14-16 Oct. 2011

Firstpage

486

Lastpage

491

Abstract

The Bayesian Networks are graphical models that are easy to interpret and update. These models are useful if the knowledge is uncertain, but they lack some means to express ambiguity. To face this problem, we propose Fuzzy Evidence in Bayesian Networks and combine the Fuzzy Logic and Bayesian Network. This has allowed to benefit from mutual advantages of these two approaches, and to overcome the problem of data and observation ambiguity. This paper proposes an inference algorithm which uses the Bayesian Network and Fuzzy Logic reliability. This solution has been implemented, tested and evaluated in comparison with the existing methods.

Keywords

belief networks; fuzzy logic; fuzzy reasoning; fuzzy set theory; graph theory; Bayesian network; data ambiguity; fuzzy evidence; fuzzy logic reliability; graphical models; inference algorithm; observation ambiguity; Bayesian methods; Fuzzy logic; Fuzzy systems; Inference algorithms; Junctions; Probability distribution; Uncertainty; Artificial Intelligence; Bayesian Networks; Fuzzy Logic; Uncertain Evidence;

fLanguage

English

Publisher

ieee

Conference_Titel

Soft Computing and Pattern Recognition (SoCPaR), 2011 International Conference of

Conference_Location

Dalian

Print_ISBN

978-1-4577-1195-4

Type

conf

DOI

10.1109/SoCPaR.2011.6089143

Filename

6089143