Title :
Information fusion of multi-fuzzy information systems
Author :
Tao Feng ; Libo Feng
Author_Institution :
Coll. of Sci., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
Abstract :
This paper discusses the fusion of multi-fuzzy information systems and hypotheses choice. First, the basic definitions and properties of fuzzy rough sets, belief and plausibility functions and entropy are reviewed. Then, we study the fusion method for multi-fuzzy information systems. Finally, we define the entropy of multi-fuzzy information systems and the conditional entropy of multi-fuzzy information systems given by a hypothesis, and make choice for the optimal hypotheses of the universe of discourse.
Keywords :
belief networks; entropy; fuzzy set theory; information systems; optimisation; rough set theory; sensor fusion; belief functions; conditional entropy; fusion method; fuzzy rough sets; hypotheses choice; information fusion; multifuzzy information systems; optimal hypotheses; plausibility functions; Approximation methods; Educational institutions; Entropy; Finite element analysis; Information systems; Rough sets; Uncertainty; conditional entropy; granular;entropy; information fusion;
Conference_Titel :
Granular Computing (GrC), 2013 IEEE International Conference on
Conference_Location :
Beijing
DOI :
10.1109/GrC.2013.6740388
