Measure information quality of basic probability assignment: An information volume method

摘要

Information quality is a concept that can be used to measure the information of probability distribution. Dempster-Shafer evidence theory can describe uncertain information more reasonably than probability theory. Therefore, it is a research hot spot to propose information quality applicable to evidence theory. Recently, Deng proposed the concept of information volume based on Deng entropy. It is worth noting that, compared with the Deng entropy, the information volume of the Deng entropy contains more information. Obviously, it may be more reasonable to use the information volume of Deng entropy to represent uncertain information. Therefore, this article proposes a new information quality, which is based on the information volume of Deng entropy. In addition, when the basic probability assignment (BPA) degenerates into a probability distribution, the proposed information quality is consistent with the information quality proposed by Yager and Petry. What’s more, based on the information quality of information volume, a correlation coefficient is proposed. After that, several numerical examples illustrate the effectiveness of this new method. Finally, a weight average fusion method based on information quality of information volume is proposed, and a target recognition task and a pattern recognition experiment are used to illustrate the efficiency of the method.