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Fuzzy set theory, an extension of classical set theory, is used to deal with the so-called fuzzy sets whose members are ambiguous.

本文基于可信性理论，对模糊变量的熵进行了详尽的分析和研究。

In order to process incomplete information systems, the classical rough set theory needs to be extended to some unequal relation.

需要将经典的粗糙集理论不可分辨关系加以扩充才能处理不完备信息系统。

In contrast to classical set theory, fuzzy set theory, which takes the uncertainty intrinsic to images as a fact, finds great success in the area of thresholding.

与经典的二值集合理论相比，模糊集理论因为考虑了图象所固有的不确定性而在门限化领域获得了很大的成功，受到了广泛的重视。

After analyze some kinds of extensions to the classical rough set theory, a new extension of rough set model based on limited non-symmetric similarity relation is developed.

为此，在分析研究已有的扩充粗糙集理论模型的基础上，进一步提出基于限制非对称相似关系的扩充粗糙集模型。

The classical Rough Set Theory requires a complete or correct system when the system involves assorting. But in fact, it is sometimes unavoidable for the system to contain noise data.

Pawlak提出的粗集模型处理的分类必须是完全正确的或肯定的，但在实际应用中，数据中包含噪音是难免的。

Fuzzy set, Vague set and C(superscript *)-fuzzy set are extension of classical set theory. They are also results of fuzzy set theory development.

模糊集、Vague集和C-模糊集都是对经典集合论的扩展，同时又是模糊集合论分支的发展成果。

Rough Set theory is an useful tool to process inaccurate data. But classical rough set theory is not good enough to solve these problems when original data is fuzzy or indefinite.

但是在实际生活中，存在许多模糊现象不能简单地用传统理论精确地刻画，如何表示和处理这些现象是数据挖掘研究中的重要问题。

Considering that the classical rough set theory can only process the discrete data, the degree of general importance of an attribute and attribute subsets was presented. And then a generalization rough set theory was proposed based on the general near neighborhood relation.

针对经典粗糙集理论仅能处理离散化数据的局限性，提出属性和属性子集的广义重要度的概念以及空间中的广义近邻关系，并提出了广义近邻关系下的广义粗糙集扩展模型。

As a generalization of the classical set theory, thetheory of rough sets have successfully applied in many fields of artificial intelligence,such as machine learning, malfunction diagnosis, decision analysis, process controland knowledge discovery in databases.

Pawlak于1982年提出的一种数据分析理论。该理论是经典集合论的一种推广，已经成功地应用于机器学习、故障诊断、分析决策、过程控制以及关系数据库中的知识获取等人工智能领域。

In classical rough set theory,a target concept can usually be depicted via static granulation,which cannot well characterize dynamic cognitive process in problem solving.

经典的粗糙集理论刻画目标概念运用静态的粒度分析，不便于刻画人们问题求解的动态认知过程。

Tom: You are right, he worked hard all the time.

你是对的。他一直都是努力工作。

Take shortcomings,failures,and mockings of others as commonplace and a drive to complete oneself,hold your own opinion over the evalution and disscution divested from others,afterwards sink into the state of eliminate mistakes if any or encourge oneself being not being influenced by the sayinngs of others or having no ideas to do.

把缺点、失败及别人的耻笑等看成是一种常事，当成完善自己的动力，对别人的评价和议论自己心中有主见，做到&有则改之，无则加勉&，不为人言所左右或无所适从。