模糊粗糙集中综合评价的属性约简和规则获取

Attribute Reduction and Rule Generation of Comprehensive Evaluation in Fuzzy Rough Set

传统的评价方法在进行评价之前没有进行属性约简,并且对新样本的评价过程过于复杂。鉴于此,运用(S,T)模糊粗糙集对综合评价中的属性约简和规则获取进行了研究,通过属性约简精简评价指标,通过规则获取来简化新样本的评价过程,为新样本的评价提供了一种全新的方法。最后以一个综合评价实例来演示如何进行属性约简和规则获取。

Traditional evaluation methods do not actualize attribute reduction before evaluation, and evaluation process is too complex to new samples. This paper has studied attribute reduction and rule generation in comprehensive evaluation making use of the （S, T）fuzzy rough set. Attribute reduction is to optimize evaluating index and rule generation is to simplify calculation process, so a new method is provided to evaluation of new samples. At last, the paper gives an example of comprehensive evaluation to demonstrate the process of attribute reduction and rule generation.