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Can fuzzy entropies be effective measures for evaluating the roughness of a rough set?

机译:模糊熵可以作为评估粗糙集粗糙度的有效措施吗?

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The roughness of a rough set arises from the existence of its boundary region. In such a boundary region, each object has a non-zero rough membership degree. When an object's rough membership degree is regarded as its fuzzy membership degree, a rough set can induce a fuzzy set. This relationship motivates us to assert that there may exist some inherent relations between the roughness of a rough set and the fuzziness of the fuzzy set induced from the rough set. This assertion leads us to the question: Can the existing fuzzy entropies be used to evaluate the roughness of a rough set? To answer this question, we first analyze how the boundary region varies when the partition of the universe becomes coarser, and then exploit this analysis in the introduction of a more appropriate definition on the roughness of a rough set. To determine whether a fuzzy entropy can be used to evaluate the roughness of a rough set or not, we develop three methods for estimating the ability of a fuzzy entropy to measure the roughness. The experiments show that these methods are very effective and can be applied to select a fuzzy entropy as a measure of the roughness of a rough set.
机译:粗糙集的粗糙度由其边界区域的存在引起。在这样的边界区域中,每个对象具有非零的粗隶属度。当一个对象的粗糙隶属度被认为是它的模糊隶属度时,一个粗糙集可以引起一个模糊集。这种关系促使我们断言在粗糙集的粗糙度和由粗糙集引起的模糊集的模糊性之间可能存在某些固有关系。这个断言引出了我们一个问题:现有的模糊熵可以用于评估粗糙集的粗糙度吗?为了回答这个问题,我们首先分析当宇宙的划分变得更粗糙时边界区域是如何变化的,然后在引入关于粗糙集的粗糙度的更合适定义的介绍中利用这一分析。为了确定模糊熵是否可用于评估粗糙集的粗糙度,我们开发了三种方法来估计模糊熵测量粗糙度的能力。实验表明,这些方法非常有效,可用于选择模糊熵作为粗糙集粗糙度的度量。

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