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Qualitative rules mining and reasoning based on cloud model

机译:基于云模型的定性规则挖掘与推理

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Qualitative rules mining and reasoning is one of the important aspects of data mining and knowledge discovery. Backward cloud can transform quantitative values into qualitative concept naturally, and the rule generator constructed by cloud model can describe qualitative rules expressing by natural language effectively. In this paper, we employ backward cloud to obtain qualitative rules from a small quantity of precise cases, and construct rule generator to provide a reasoning mechanism. Finally, qualitative rules mining and reasoning approach is used to control the electrical machine running speed under practical working conditions, which demonstrates the validity of the cloud method.
机译:定性规则的挖掘和推理是数据挖掘和知识发现的重要方面之一。后向云可以自然地将定量值转化为定性概念,云模型构造的规则生成器可以有效地描述自然语言表达的定性规则。在本文中,我们使用后向云从少量精确案例中获取定性规则,并构造规则生成器以提供推理机制。最后,采用定性规则挖掘和推理方法控制电机在实际工况下的运行速度,证明了云法的有效性。

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