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The study on alternative combination rules in Dempster-Shafer theory (DST) when evidences are in conflict has emerged again recently as an interesting topic, especially in data/information fusion applications. The earlier researches have mainly focused on investigating the alternative which would be appropriate for the conflicting situation, under the assumption that a conflict is identified. However, the current research shows that not only the combination rule but also the classical conflict coefficient in DST are not correct to determine the conflict degree between two pieces of evidences. Most existing methods of measuring conflict do not consider the open world situation, whose frame of discernment is incomplete. To solve this problem, a new conflict representation model to determine the conflict degree between evidences is proposed in the generalized power space, which contains two parameters: the conflict distance and the conflict coefficient of inconsistent evidences. This paper argues that only when the conflict measure value in the new representation model is high, it is safe to say the evidences are in conflict. Experiments illustrate the efficiency of the proposed conflict representation model.
The study on alternative combination rules in Dempster-Shafer theory (DST) when evidences are in conflict has recently again recently as an interesting topic, especially in data / information fusion applications. The earlier researches have moderate focused on investigating the alternative which would be appropriate for the conflicting situation, under the assumption that a not only the combination rule but also the classical conflict coefficient in DST are not correct to determine the conflict degree between two pieces of evidences. Most existing methods of measuring conflict do not consider the open world situation, whose frame of discernment is incomplete. To solve this problem, a new conflict representation model to determine the conflict degree between evidences is proposed in the generalized power space, which contains two parameters: the conflict distance and the conflict coefficient of inconsistent evidences. This pape r argues that only when the conflict measure value in the new representation model is high, it is safe to say the evidences are in conflict. Experiments illustrate the efficiency of the proposed conflict representation model.