利用三角模糊数的语言变量项集减项算法

An n-fold reduction of linguistic variables based on the triangular fuzzy numbers

现有基于模糊语言变量的信息系统风险评估方法的运行,一般需要在相关领域专家协助下产生由标准参数梯形模糊数描述的语言变量项集,此类方法的实践有效性往往取决于其在专家无法参与的情况下处理不同类型模糊数以及变化的语言变量项集的能力。该文提出了一种利用三角模糊数的n阶语言变量项集减项算法,并采用4类典型的语言变量三角模糊数对该方法的正确性进行验证。结果表明:在无需相关领域专家介入的情况下,该方法能够实现n阶语言变量项集等价变换过程的自动化,为现有的信息安全风险评估系统的改进提供了方法。

Existing information system risk assessment methods based on fuzzy language variables generally requires that the language variable itemsets generated by the standard parameter trapezoidal fuzzy numbers which are generated by experts in the field. The effectiveness of this approach then often depends on its ability to deal with different types of fuzzy numbers and changing linguistic variable itemsets when the expert cannot participate. This study presents a method for an n-fold reduction of the linguistic variables based on the triangular fuzzy numbers that is validated using four types of fuzzy numbers for language variables. The results show that the method automates the equivalent transformation of n fold language variable items without expert intervention to improve information security risk assessment systems.