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首页> 外文期刊>International Journal of Uncertainty, Fuzziness, and Knowledge-based Systems >ENTROPIES OF FUZZY INDISCERNIBILITY RELATION AND ITS OPERATIONS
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ENTROPIES OF FUZZY INDISCERNIBILITY RELATION AND ITS OPERATIONS

机译:模糊不可分割关系的熵及其操作

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摘要

Yager's entropy was proposed to compute the information of fuzzy indiscernibility relation. In this paper we present a novel interpretation of Yager's entropy in discernibility power of a relation point of view. Then some basic definitions in Shannon's information theory are generalized based on Yager's entropy. We introduce joint entropy, conditional entropy, mutual information and relative entropy to compute the information changes for fuzzy indiscemiblity relation operations. Conditional entropy and relative conditional entropy are proposed to measure the information increment, which is interpreted as the significance of an attribute in fuzzy rough set model. As an application, we redefine independency of an attribute set, reduct, relative reduct in fuzzy rough set model based on Yager's entropy. Some experimental results show the proposed approach is suitable for fuzzy and numeric data reduction.
机译:提出使用雅格熵来计算模糊不可分辨关系的信息。在本文中,我们以关系观点的可分辨性提出了对Yager熵的新颖解释。然后根据Yager的熵,概括了香农信息理论的一些基本定义。我们引入联合熵,条件熵,互信息和相对熵来计算模糊不可分关系运算的信息变化。提出了条件熵和相对条件熵来度量信息的增量,这被解释为模糊粗糙集模型中一个属性的意义。作为应用,我们在基于Yager熵的模糊粗糙集模型中重新定义属性集,归约,相对归约的独立性。实验结果表明,该方法适用于模糊和数值数据的约简。

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