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Journal of Sensors
Volume 2015, Article ID 509385, 9 pages
http://dx.doi.org/10.1155/2015/509385
Research Article

Combination of Evidence with Different Weighting Factors: A Novel Probabilistic-Based Dissimilarity Measure Approach

Key Laboratory of Embedded and Network Computing of Hunan Province, College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China

Received 9 October 2014; Revised 9 February 2015; Accepted 23 February 2015

Academic Editor: Stefania Campopiano

Copyright © 2015 Mengmeng Ma and Jiyao An. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. B. Khaleghi, A. Khamis, F. O. Karray, and S. N. Razavi, “Multisensor data fusion: a review of the state-of-the-art,” Information Fusion, vol. 14, no. 1, pp. 28–44, 2013. View at Publisher · View at Google Scholar · View at Scopus
  2. A. P. Dempster, “A generalization of Bayesian inference (with discussion),” Journal of the Royal Statistical Society, Series B: Methodological, vol. 30, no. 2, pp. 205–247, 1968. View at Google Scholar · View at MathSciNet
  3. G. Shafer, A Mathematical Theory of Evidence, Princeton University Press, Princeton, NJ, USA, 1976. View at MathSciNet
  4. Y. Xia and M. S. Kamel, “Novel cooperative neural fusion algorithms for image restoration and image fusion,” IEEE Transactions on Image Processing, vol. 16, no. 2, pp. 367–381, 2007. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  5. M. Fontani, T. Bianchi, A. D. Rosa, A. Piva, and M. Barni, “A framework for decision fusion in image forensics based on Dempster-Shafer theory of evidence,” IEEE Transactions on Information Forensics and Security, vol. 8, no. 4, pp. 593–607, 2013. View at Publisher · View at Google Scholar · View at Scopus
  6. W. Huang and Z. L. Jing, “Multi-focus image fusion using pulse coupled neural network,” Pattern Recognition Letters, vol. 28, no. 9, pp. 1123–1132, 2007. View at Publisher · View at Google Scholar · View at Scopus
  7. A. M. Aziz, “A new multiple decisions fusion rule for targets detection in multiple sensors distributed detection systems with data fusion,” Information Fusion, vol. 18, no. 1, pp. 175–186, 2014. View at Publisher · View at Google Scholar · View at Scopus
  8. O. Basir and X. H. Yuan, “Engine fault diagnosis based on multi-sensor information fusion using Dempster-Shafer evidence theory,” Information Fusion, vol. 8, no. 4, pp. 379–386, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. B. Scotney and S. McClean, “Database aggregation of imprecise and uncertain evidence,” Information Sciences, vol. 155, no. 3-4, pp. 245–263, 2003. View at Publisher · View at Google Scholar · View at Scopus
  10. L. A. Zadeh, “A simple view of the Dempster-Shafer theory and its implications for the rule of combination,” Artificial Intelligence, vol. 2, no. 7, pp. 85–90, 1986. View at Google Scholar
  11. E. Lefevre, O. Colot, and P. Vannoorenberghe, “Belief function combination and conflict management,” Information Fusion, vol. 3, no. 2, pp. 149–162, 2002. View at Publisher · View at Google Scholar · View at Scopus
  12. R. R. Yager, “On the Dempster-Shafer framework and new combination rules,” Information Sciences, vol. 41, no. 2, pp. 93–137, 1987. View at Publisher · View at Google Scholar · View at MathSciNet
  13. W. Q. Wang, Y. J. Zhao, and J. Huang, “A new evidence combination scheme for decision assistant,” in Proceedings of the 4th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC '12), pp. 53–57, October 2012. View at Publisher · View at Google Scholar · View at Scopus
  14. C. K. Murphy, “Combining belief functions when evidence conflicts,” Decision Support Systems, vol. 29, no. 1, pp. 1–9, 2000. View at Publisher · View at Google Scholar · View at Scopus
  15. Y. Deng, W. K. Shi, Z. F. Zhu, and Q. Liu, “Combining belief functions based on distance of evidence,” Decision Support Systems, vol. 38, no. 3, pp. 489–493, 2004. View at Publisher · View at Google Scholar · View at Scopus
  16. A. L. Jousselme, D. Grenier, and É. Bossé, “A new distance between two bodies of evidence,” Information Fusion, vol. 2, no. 2, pp. 91–101, 2001. View at Publisher · View at Google Scholar · View at Scopus
  17. W. Liu, “Analyzing the degree of conflict among belief functions,” Artificial Intelligence, vol. 170, no. 11, pp. 909–924, 2006. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  18. S.-J. Qu, Y.-M. Cheng, Q. K. Pan, Y. Liang, and S.-W. Zhang, “Conflict-redistribution DSmT and new methods dealing with conflict among evidences,” Control and Decision, vol. 24, no. 12, pp. 1856–1859, 2009. View at Google Scholar · View at Scopus
  19. Z.-G. Liu, J. Dezert, Q. Pan, and G. Mercier, “Combination of sources of evidence with different discounting factors based on a new dissimilarity measure,” Decision Support Systems, vol. 52, no. 1, pp. 133–141, 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. M. Oussalah, “On the use of Hamacher's t-norms family for information aggregation,” Information Sciences, vol. 153, pp. 107–154, 2003. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  21. P. Smets, “Decision making in the TBM: the necessity of the pignistic transformation,” International Journal of Approximate Reasoning, vol. 38, no. 2, pp. 133–147, 2005. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  22. W. Jang, A. Zhang, and D. Duanmu, “A novel probability transform method for decision making,” in Proceedings of the 3rd Chinese Information Fusion Conference, pp. 110–114, August 2011.
  23. B. R. Cobb and P. P. Shenoy, “On the plausibility transformation method for translating belief function models to probability models,” International Journal of Approximate Reasoning, vol. 41, no. 3, pp. 314–330, 2006. View at Publisher · View at Google Scholar · View at MathSciNet
  24. L. A. Zadeh, “Fuzzy sets,” Information and Computation, vol. 8, no. 1, pp. 338–353, 1965. View at Google Scholar · View at MathSciNet