模糊蕴涵算子的不确定性特征提取及其应用研究

Research on Uncertainty Feature Extraction of Fuzzyimplication Operators and Its Application

针对现有模糊蕴涵算子关于不确定性特征的描述均是以实数形式进行,无法体现不确定性,本文基于合成推理规则,首次提出模糊关系区间熵的定义并建立具体的度量形式,然后建立基于区间熵的模糊蕴涵算子排序方法,并利用具体算例对该方法进行实例分析。本文的研究结果为模糊控制器中模糊蕴涵算子的选择提供理论依据。

In this paper,a novel feature of fuzzy relations is proposed to realize the fuzziness measurement of the fuzzy relation.The feature value is extracted from the interval number instead of a real number,which is different from the existing features of fuzzy relations,can be used to describe the uncertainty of the fuzzy relation more accurately and comprehensively.And then,based on the feature,a new ranking method of fuzzy implication operators is proposed.Utilizing the method,some classical operators can be ranked better,which shows that the proposed feature can be viewed as a more reasonable index to measure the fuzzy implication operators.The achievements in the presented work will provide another theoretical basis for selecting operators in constructing fuzzy system and lay a solid foundation for further researches.