模糊信息的复合型处理机制

Compound processing mechanism for fuzzy information

通过水平截集将模糊信息局部清晰化是生产线优化调度等实际领域中常用的方法。该文针对模糊信息之间的差异度量问题,在分析了现有度量方法不足的基础上,引入了一种描述水平可靠程度的参数——水平可靠性函数,并从模糊数的水平截集和隶属函数出发,给出了几种水平可靠性函数;进而通过可靠统计量建立了一种带有可靠程度的衡量模糊数之间差异的度量机制,并结合实例给出了建立这种度量机制的方法和步骤。分析结果表明这种度量机制是现有模糊度量的完善,并将为模糊信息处理的决策和优化提供理论基础。

Fuzzy information problems are often transformed into locally clear problems by using level cut sets in many fields such as manufacturing system production line scheduling with uncertainties. However, current metric methods can not adequately depict the difference between fuzzy numbers. This paper introduces a parameter which describes the reliability of level cut sets called the level reliability function and gives some level reliability functions for level cut sets and membership functions of fuzzy numbers. The reliability is then combined with a metric method to form a compound metric mechanism that more effectively describes the defference between fuzzy number, and with an example describing the method the for building this compound metric mechanism. The results show that the compound metric mechanism complements current fuzzy metrics as a theoretical basis for optimization and decisionmaking in fuzzy information processing.