Determining Truth Degrees of Input Places in Fuzzy Petri Nets
针对模糊Petri网中初始真值通常由研究者直接给定的问题，提出一种基于犹豫二元语言术语集的群体决策模型，利用领域专家知识和数据确定输入位置的真值，并通过数值示例验证其有效性。
Fuzzy Petri net (FPN), as one type of high-level Petri nets, has attracted a lot of attention over the recent decade due to its adequacy for knowledge representation and logic reasoning. However, in the FPN literature, the truth degrees of input places are usually given directly or supposed by researchers. No or little research has been performed on the determination of initial marking vector for a specific FPN. In this correspondence paper, we introduce a group decisionmaking model using hesitant 2-tuple linguistic term sets to obtain the initial truth values of FPNs based on domain experts' knowledge and gathered data. As is illustrated by the numerical example, the proposed framework can well capture domain experts' diversity judgements and derive initial truth degrees for an FPN under different types of uncertainties.