Sign fusion of multiple QPNs based on qualitative mutual information

In the era of big data, the fusion of uncertain information from different data sources is a crucial issue in various applications. In this paper, a sign fusion method of multiple qualitative probabilistic networks (QPNs) with the same structure from different data sources is proposed. Specifically, firstly, the definition of parallel path in multiple QPNs is given and the problem of fusion ambiguity is described. Secondly, the fusion operator (circle plus(f)-operator) theorem is introduced in detail, including its proof and algebraic properties. Further, an efficient sign fusion algorithm is proposed. Finally, experimental results demonstrate that our fusion algorithm is feasible and efficient.