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A Study on Efficient Knowledge Discovery by Fuzzy Classifier SystemUtilizing Symbolic Information

机译:模糊分类器Systeilize符号信息有效知识发现的研究

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摘要

This paper presents a Fuzzy Classifier Sys-tem(FCS) which can discover fuzzy rules efficiently. The system translates human's knowledge into symbolic information, and effectively limits its search space for the fuzzy rules by utilizing the symbols. The system can also extracts symbolic information from the acquired fuzzy rules for efficient exploration of another new fuzzy rules. Simulations are done to demonstrate the capability of the proposed method.
机译:本文提出了一种模糊分类器SYS-TEM(FCS),可以有效地发现模糊规则。该系统将人类的知识转化为象征性信息,并通过利用符号来有效地限制模糊规则的搜索空间。该系统还可以从获取的模糊规则中提取符号信息,以便有效探索另一个新的模糊规则。完成模拟以证明所提出的方法的能力。

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