An integrated information fusion approach based on the theory of evidence and group decision-making

Authors:
Yee Leung;Nan-Nan Ji;Jiang-Hong Ma
Affiliations:
Department of Geography and Resource Management, Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong;School of Mathematics and Statistics, Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi'an Jiaotong University, Xi'an 710049, China;Department of Mathematics and Information Science, Chang'an University, Xi'an 710041, Shaanxi, China
Venue:
Information Fusion
Year:
2013

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Abstract

Dempster-Shafer theory of evidence has been employed as a major method for reasoning with multiple evidence. The Dempster's rule of combination is however incapable of managing highly conflicting evidence coming from different information sources at the normalization step. Extending current rules, we incorporate the ideas of group decision-making into the theory of evidence and propose an integrated approach to automatically identify and discount unreliable evidence. An adaptive robust combination rule that incorporates the information contained in the consistent focal elements is then constructed to combine such evidence. This rule adjusts the weights of the conjunctive and disjunctive rules according to a function of the consistency of focal elements. The theoretical arguments are supported by numerical experiments. Compared to existing combination rules, the proposed approach can obtain a reasonable and reliable decision, as well as the level of uncertainty about it.