In order to match the case in this situation, a fuzzy similarity function between case-target and Case-base was constructed based on the conception of membership degree and closeness degree.

为了在该情况下进行实例匹配，基于隶属度和贴近度的概念，构造了靶实例与基实例的模糊相似度函数，从而以统一形式同时处理上述两类数据。

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Then optimization model with the membership degree is constructed. It is solved by using genetic algorithms with dynamical castigatory function.

然后结合隶属度变量构建优化模型，利用具有动态惩罚函数的遗传算法求解，计算得到各方案的所属类别。

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This paper introduces membership function into fuzzy queries, and presents membership degree which can reflect its fuzziness in the query result.

将隶属函数引入模糊查询中，提出能在查询结果中反映查询模糊性的隶属度。

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