Modelling uncertainty in multisensory systems at conflict measurements with dempstershafer combinatorial rule

  • 1 Institute of Metal Science, Equipment and Technology with Hydroaerodynamic Center at Bulgarian Academy of Sciences, Bulgaria


Decision making in conflict data is a problem that plague the information fusion. It is usually resolved by the use of probabilistic methods such as Bayes. Still Bayes becomes impractical in strong presence of conflicts or lack of data. In that case Dempster–Shafer (DS) evidence theory is applied, because of its ability to handle conflicting sensor inputs. Because of that, DS-based information fusion is very popular in decision-making applications, although the classic combinatorial rule may produce counter intuitive results, especially when combining evidences with high level of conflict. The paper present a method which can be applied to the decision making process, thus resolving this problem.



  1. Shafer, G. A Mathematical Theory of Evidence. Princeton University Press: Princeton. NJ. USA, 1976. Volume 42.
  2. Fourati, H. Multisensor Data Fusion: From Algorithms and Architectural Design to Applications. CRC Press: Boca Raton. FL. USA . 2015.
  3. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. in Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, vol.1.IEEE, 2005, pp. 886–893.
  4. Coombs, K. Freel. D.; Lampert. D.; Brahm. S.J. Sensor Fusion: Architectures. Algorithms. and ApplicationsIII. Int. Soc. Opt. Photonics 1999. 3719. 103– 15. pp. 2895–2907, 2003.
  5. Dempster, A.P. Upper and Lower Probabilities Induced by a Multivalued Mapping, in Classic Works of the Dempster-Shafer Theory of Belief Functions; Springer: Berlin/Heidelberg, Germany, 2008; pp. 57–72.6. Yager, R.R. On the Dempster-Shafer framework and new combination rules. Inf. Sci. 1987, 41, 93–137.
  6. Yager, R.R. On the Dempster-Shafer framework and new combination rules. Inf. Sci. 1987, 41, 93–137.

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