论文标题
通过满足GMP规则的聚合功能的近似推理
Approximate reasoning with aggregation functions satisfying GMP rules
论文作者
论文摘要
为了加强模糊模糊元素（FMP）和模糊模式托伦斯（FMT）问题的近似推理的有效性，开发了三个具有聚合功能的近似推理方案，并在本文中分别研究了它们的有效性。我们首先研究了聚集函数产生的模糊含义的某些特性。然后呈现$ a $ compositional的推理规则（ACRI），作为Zadeh CRI的扩展，通过聚合功能代替$ t $ norm。进一步讨论了基于相似性的基于相似性的近似推理。此外，我们提供五重奏的含义原理（QIP）方法，具有汇总函数来解决FMP和FMT问题。最后，我们提出的三种近似推理方法的有效性分别使用GMP规则详细分析。
To strengthen the effectiveness of approximate reasoning in fuzzy modus ponens (FMP) and fuzzy modus tollens (FMT) problems, three approximate reasoning schemes with aggregation functions are developed and their validity is respectively investigated in this paper. We firstly study some properties of fuzzy implication generated by aggregation function. And then present an $A$-compositional rule of inference (ACRI) as an extension of Zadeh's CRI replacing $t$-norm by an aggregation function. The similarity-based approximate reasoning with aggregation functions is further discussed. Moreover, we provide the quintuple implication principle (QIP) method with aggregation functions to solve FMP and FMT problems. Finally, the validity of our proposed three approximate reasoning approaches is respectively analyzed using GMP rules in detail.
