Title :
A scheme for constructing evidence structures in Dempster-Shafer evidence theory for data fusion
Author :
Zhu, Hongwei ; Basir, Otman
Author_Institution :
Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada
Abstract :
This paper addresses the issue of evidence structure construction involved in the Dempster-Shafer evidence theory (DSET) based reasoning for data fusion. An in-depth study is carried out on the properties of the proposed Proportional Difference Evidence Structure Constructing Scheme (PDESCS). Some properties have been mathematically proved for the PDESCS associated DSET. If PDESCS is applied to probabilistic evidence, in terms of posterior probability distributions, the DSET based reasoning with the maximum commonality decision making scheme is equivalent to the Beyesian approach with the maximum a posteriori probability principle (MAP). If PDESCS is applied to fuzzy evidence, in terms of fuzzy sets, the DSET based reasoning is equivalent to applying the maximum fuzzy membership decision making scheme to the intersected fuzzy set by the product T-norm operator. If PDESCS is applied to both probabilistic evidence and fuzzy evidence, the DSET based reasoning is equivalent to applying the maximum fuzzy set probability decision making scheme. To show the effectiveness of the PDESCS associated DSET, experiments are carried out for classifying human brain MR (magnetic resonance) images. It is concluded that the proposed scheme works well, and provides not only a unified framework to accommodate probabilistic evidence and fuzzy evidence, but also an effective reasoning mechanism to deal with different uncertainty, in terms of randomness and fuzziness, as well as precision.
Keywords :
Bayes methods; biomedical MRI; case-based reasoning; decision making; fuzzy set theory; probability; sensor fusion; Bayesian approach; Dempster-Shafer evidence theory; T-norm operator; data fusion; fuzzy evidence; fuzzy set; human brain images; magnetic resonance images; maximum aposteriori probability principle; maximum fuzzy membership decision making scheme; probabilistic evidence; probability distributions; proportional difference evidence structure construction; proportional difference scheme; reasoning mechanism; Data engineering; Decision making; Design engineering; Fuzzy reasoning; Fuzzy sets; Histograms; Maximum a posteriori estimation; Probability distribution; Systems engineering and theory; Uncertainty;
Conference_Titel :
Computational Intelligence in Robotics and Automation, 2003. Proceedings. 2003 IEEE International Symposium on
Print_ISBN :
0-7803-7866-0
DOI :
10.1109/CIRA.2003.1222309