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为解决相似案例差异性问题，提出了基于划分聚类和模糊神经网络的设计案例相似性检索方法。
To improve the diversity of similar cases, similarity retrieval method based on partitioned clustering and General Fuzzy Min-Max neural network is developed.
其中模糊集理论被用来进行相似性匹配从而降低噪音在案例检索时的干扰，SCBR技术用来实施对案例的修改和重用。
Fuzzy set theory was employed to perform approximate matching and thus to reduce potential noise in case retrieval, and the SCBR technology was used to implement the adaptation and reuse for case.
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