Entailment for measure‐based belief structures can extend the possible probability value range of variables on a space and obtain more information from variables. However, if the variable space comes from intuitionistic fuzzy sets, the classical entailment for measure‐based belief structures will not work in this issue. To deal with this situation, we propose the entailment for intuitionistic fuzzy sets based on generalized belief structures in this paper to apply the entailment for measure based belief structures on space, which is made up of non‐membership degree, membership degree and hesitancy degree of a given intuitionistic fuzzy sets. Numerical examples are mentioned to prove the effectively and flexibility of this proposed entailment model. The experimental results indicate that the proposed algorithm can extend the possible probability value range of variables of space efficiently and obtain more information from intuitionistic fuzzy sets.

中文翻译：

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基于广义信念结构的直觉模糊集的蕴涵

基于度量的信念结构的蕴含可以扩展空间上变量的可能概率值范围，并从变量中获取更多信息。然而，如果变量空间来自直觉模糊集，那么基于度量的信念结构的经典蕴涵在这个问题上将不起作用。针对这种情况，本文提出了基于广义信念结构的直觉模糊集的蕴涵，将基于度量的信念结构的蕴涵应用到空间上，由非隶属度、隶属度和犹豫度组成。给定的直觉模糊集。数值例子证明了所提出的蕴涵模型的有效性和灵活性。