并将新的模糊隶属度模型引入自适应支持向量机，提出了模糊自适应支持向量机算法。

Introducing the novel fuzzy membership model into Adaptive Support Vector Machine (ASVM), we propose an Adaptive fuzzy Support Vector Machine algorithm (AFSVM).

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此模型通过计算研究对象所属的各个已知模式的相对隶属度和级别特征值，判断了研究对象的分属模式。

The model can recognize research object pattern by counting its relative membership value to known patterns and its status value.

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本文简介了丰度模型、齐波夫律、特征分析、信息量与隶属函数等方法，并对其中某些方法有所改进。

In this paper, several methods such as abundance pattern, Zipf's Law, characteristic analysis, information content and subordinate function are briefly introduced and Some of them are improved.

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