将学习矢量量化神经网络集成在基于实例推理的故障诊断方法中，减小了实例搜索空间，提高了实例检索效率。

The learning vector quantization neural network has been integrated successfully with the case-based reasoning approach to reduce the case indexing space and to enhance the indexing efficiency.

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针对基于实例的产品方案设计问题，提出了一种半自动的、具有自学习功能的实例修改策略。

Aiming at the problem of case-based preliminary product design, this paper presents a semi-automatic case revisal strategy that has a self-learning capability.

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仍然有些算法很容易就可以被归入好几个类别，好比学习矢量量化，它既是受启发于神经网络的方法，又是基于实例的方法。

There are still algorithms that could just as easily fit into multiple categories like Learning Vector Quantization that is both a neural network inspired method and an instance-based method.

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