Şensoy, MuratKaplan, L.Ayci, Gönülde Mel, G.2016-02-152016-02-152015978-098244386-6http://hdl.handle.net/10679/2151Due to copyright restrictions, the access to the full text of this article is only available via subscription.Information is critical in almost all decision making processes. Therefore, it is important to get the right information at the right time from the right sources. However, information sources may behave differently while providing information - i.e., they may provide unreliable, erroneous, noisy, or misleading information deliberately or unintentionally. Motivated by this observation, in this paper, we propose a statistical information fusion approach based on behavior estimation. Our approach transforms the conveyed information into more useful form by tempering them with the estimated behaviors of sources. Through extensive simulations, we have shown that our approach has a lower computational complexity, and achieves significantly low behavior estimation and fusion errors.enginfo:eu-repo/semantics/restrictedAccessConference paper558565000389523300075Information fusionSubjective logicDirichlet distributionsBehavior estimation2-s2.0-84960539337