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Level identification using input data mining for hierarchical fuzzy system

机译:使用输入数据挖掘进行层次模糊系统的级别识别

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Fuzzy rule based Systems have been very popular in many control applications. However, when fuzzy control Systems are used in real problems, many rules may be required. Hierarchical fuzzy system that partitions a problem for more efficient computation may be the answer. In the stages of creating a hierarchical fuzzy system, level identification stage is a crucial and time consuming one. This has the direct effect on how efficient is the hierarchical fuzzy system. This paper has reported the use of input data mining technique to efficiently perform the level identification stage. Without the use of the input data mining, k*(k-1) ways of building the hierarchical fuzzy system have to be tried.
机译:基于模糊的规则系统在许多控制应用中非常流行。但是,当在实际问题中使用模糊控制系统时,可能需要许多规则。分区模糊系统,将问题用于更有效的计算可能是答案。在创建分层模糊系统的阶段,级别识别阶段是一个至关重要的耗时。这与分层模糊系统有多效率直接影响。本文报告使用输入数据挖掘技术有效地执行级别识别阶段。在不使用输入数据挖掘的情况下,必须尝试k *(k-1)构建分层模糊系统的方式。

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