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Solving fuzzy relation equations with max-continuous t-norm composition graphically

机译:用最大连续t范数构图求解模糊关系方程

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Fuzzy relation equations and their applications have been investigated extensively. The commonly discussed and used types usually belong to the type of max-continuous t-norms composition. This paper studies fuzzy relation equations of this type in a general meaning. The properties of the equations, especially the properties of minimal solutions and the characteristic matrix are discussed. They are closely related to the resolution of the equations. The reason why a solution could be related to a graph is revealed. It is found that all minimal solutions are determined by the characteristic matrix or the corresponding graph. And, they can be derived by the minimal coverings of the graph. Two algorithms for deriving all minimal solutions are given based on the properties of the equations and properties of the graph. Two examples are also given to demonstrate the two algorithms. Besides, the efficiency of the two algorithms and the value of the paper are discussed as well.
机译:模糊关系方程及其应用已被广泛研究。经常讨论和使用的类型通常属于最大连续t范数组成的类型。本文从一般意义上研究了这种类型的模糊关系方程。讨论了方程的性质,特别是最小解的性质和特征矩阵。它们与方程的解析度密切相关。揭示了解决方案可能与图形相关的原因。发现所有最小解均由特征矩阵或相应的图确定。并且,它们可以通过图形的最小覆盖率得出。根据方程式的性质和图的性质,给出了两种用于推导所有最小解的算法。还给出了两个例子来说明这两种算法。此外,还讨论了这两种算法的效率以及本文的价值。

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