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中文摘要：
因为机械产品方案设计评价包含诸多模糊性,所以模糊综合评价成为机械产品方案设计评价的优势模型。在模糊评价矩阵确定后,模糊评价的核心计算是隶属度转换,但是,现有的隶属度转换算法不正确,因为各指标隶属度中原本对方案分类不起作用的冗余值,也被用于计算方案隶属度。要使构建的隶属度转换方法不受冗余数据干扰,关键是弄清楚各指标隶属度究竟提供给方案怎样的分类信息。为此,用基于熵的数据挖掘方法,通过挖掘隐含在指标隶属度中关于方案分类的知识信息,理清方案分类与各指标隶属度间的关系,通过定义区分权清除指标隶属度中对方案分类不起作用的冗余值,最终确定出各指标隶属度提供给方案的分类信息,正确实现隶属度转换。由此建立机械产品方案设计模糊综合评价中隶属度转换的新算法。
英文摘要：
Because conceptual design of mechanic product has many fuzzy features, fuzzy comprehensive evaluation becomes an advantageous model. If fuzzy evaluation matrix is obtained, the key step in fuzzy evaluation is to realize membership conversion. However the existing methods are wrong, because the redundant data in index membership that are of no use in scheme classification are used to calculate scheme membership. In order to avoid this kind of interference with membership conversion, the most important thing is to ascertain the classification information from index membership for scheme classification. Thus by finding knowledge information in index membership about scheme classification, data mining based on entropy clarifies the relationship between scheme classification and index membership. Classification weight is defined to eliminate the redundant data and classification information is obtained. Membership conversion is realized accurately. Then fuzzy comprehensive evaluation for conceptual design of mechanical product based on new membership conversion is built.
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