A New Method to Measure the Information Quality Based on Shannon Entropy

Abstract

When aggregating data from multi-source uncertain information, how to increase the certainty and reduce the conflict is still an open issue. This paper proposes a new method to measure information quality based on Shannon entropy, which can be used to measure the certainty or information provided by probability distributions. Furthermore, a method to obtain information quality-fused values from different probability distributions is given, which can be used to measure the conflict when fusing probability distributions. Based on them, a probability aggregation method that considers both uncertainty and conflict is developed and applied to fault diagnosis. Two examples are given to illustrate the effectiveness of the proposed method.