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中文摘要：
提出了一种新的粗糙集双重学习方法,该方法能用遗传算法实现外层学习,用规则提取方法进行内层学习.其基本思想是：首先引入遗传算法,将属性编码,并针对不同的属性组合进行规则提取;然后用测试样本对规则集进行检验,并基于所得到的识别率建立适应度函数;最后在合适的遗传算子下获取最佳的属性组合及相应的知识规则.与其他方法相比,本文所提粗糙集双重学习方法集属性约简和规则提取于一体,整个过程具有很强的自适应能力.最后,用算例对本文方法进行了验证.
英文摘要：
A new double-layer learning method of rough set is put forward,which can carry out the outer layer learning by genetic algorithms and the inner layer learning by rule extraction.Firstly,the genetic algorithm is introduced,the attributes are coded into binary codes,and the rules are extracted under various attribute combinations.Secondly,the test samples are employed to test the obtained rules,and the fitness function is constructed on the basis of the obtained recognition rate.Finally,the optimum attribute combinations and the corresponding knowledge rules are obtained with proper genetic operators.In comparison with other methods,the presented method combines attribute reduction with rule extraction,and possesses a stronger self-adaptive ability.In the end,examples are given to verify the proposed method.
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