一种基于模糊加权均衡匹配度的区间值模糊推理方法

Interval-valued Fuzzy Reasoning Approach Based on Fuzzy Weighted-Balanced Matching Degree

在区间值模糊推理过程中,为合理地计算输入事实与规则前件的匹配程度,给出区间值模糊集的模糊加权均衡匹配度的定义,不仅考虑了每个前件分量在推理中的不同影响程度,而且考虑到每个分量匹配程度的均衡要求,进而提出一种基于模糊加权均衡匹配度的区间值模糊推理方法,并通过实例说明了该方法的有效性。

In interval-valued fuzzy reasoning, for the purpose of reasonably computing the matching degrees between inputs and ruled antecedent components, one definition was given on weight-balance matching degree and fuzzy weight of interval-valued sets, which not only put different degrees of effects on reasoning into consideration of every antecedent, but also of each component weighted-balanced matching degree. A definition was presented called fuzzy weighted-balanced matching degree between two interval-valued fuzzy sets. Furthermore, a method of interval-valued fuzzy reasoning based on fuzzy weighted-balanced matching degree was proposed. An example was given to have illustrate the function of the new approach.