This study proposes a primary node election method based on probabilistic linguistic term set (PLTS) for the practical Byzantine fault tolerance (PBFT) consensus mechanism to effectively enhance the efficiency of reaching consensus. Specifically, a novel concept of the probabilistic linguistic term set with a confidence interval (PLTS-CI) is presented to express the uncertain complex voting information of nodes during primary node election. Then, a novel score function based on the exponential semantic value and confidence approximation value for the PLTS-CI, called Score-ESCA, is used to solve the problems of comparing different nodes with various voting attitudes. This method helps select the node with the highest score by utilizing complex decision attitudes, making it an accurate primary node election solution. Furthermore, the feasibility of our proposed method is proved by both theoretical analysis and experimental evaluations.

本研究针对实用的拜占庭容错（PBFT）共识机制提出了一种基于概率语言术语集（PLTS）的主节点选举方法，以有效提高达成共识的效率。具体来说，提出了一种新的带有置信区间的概率语言术语集（PLTS-CI）概念来表达主节点选举过程中节点的不确定复杂投票信息。然后，基于PLTS-CI的指数语义值和置信度近似值的一种新颖的评分函数，称为Score-ESCA，用于解决比较具有不同投票态度的不同节点的问题。该方法利用复杂的决策态度帮助选择得分最高的节点，使其成为准确的主节点选举方案。此外，