An Efficient Method to Measure Evidence Conflict
Baojie Liu, Qingwen Yang, Xiang Wu, Yujuan Guo, Shidong Fang
Available Online June 2017.
- https://doi.org/10.2991/caai-17.2017.109How to use a DOI?
- D-S evidence theory; evidence conflict; jaccard similarity coefficient ; conflict measure; information fusion
- Dempster Shafer evidence theory, as an uncertain information fusion technology, is widely used in various fields of information fusion. However, when there is a highly conflict between two pieces of evidence, counterintuitive results are obtained by classical Dempster's combination rule. Therefore, it is very important to measure the conflict between two pieces of evidence. Based on the analysis of some typical conflict measurement methods, a new model to represent conflict was constructed with the Euclidean distance function and the Jaccard similarity coefficient. Some numerical examples illustrate that the proposed method can measure the degree of conflict between the two pieces of evidence and overcome the shortcomings of the classical conflictive coefficient, Jousselme evidence distance and Pignistic probability distance to a certain extent.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Baojie Liu AU - Qingwen Yang AU - Xiang Wu AU - Yujuan Guo AU - Shidong Fang PY - 2017/06 DA - 2017/06 TI - An Efficient Method to Measure Evidence Conflict BT - 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017) PB - Atlantis Press SP - 483 EP - 488 SN - 1951-6851 UR - https://doi.org/10.2991/caai-17.2017.109 DO - https://doi.org/10.2991/caai-17.2017.109 ID - Liu2017/06 ER -