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针对粗糙控制中控制精度不高、控制效率低等问题,提出了基于区间概念格的粗糙控制可调精度规则挖掘模型,以降低规则挖掘成本及提高应用效率.模型首先对采集到的原始数据进行预处理,使其转化成布尔型的形式背景;其次,参照一般区间概念格的生成算法进行了粗糙控制背景下的区间概念格的构造;再次,提出可调精度控制规则挖掘算法,建立了基于区间概念格的粗糙控制可调精度规则挖掘模型,最后,模型分析和实例对比验证了模型在提高规则可靠性的前提下,实现了挖掘成本和控制效率的最优化.
Aiming at the problems of low control precision and low control efficiency in rough control, a rough rules-based controllable precision rule mining model based on interval concept lattice is proposed to reduce the cost of rule mining and improve the efficiency of application.Firstly, the original data Secondly, the construction of interval concept lattice under the background of rough control is made with reference to the generation algorithm of general interval concept lattice. Thirdly, the algorithm of adjustable precision control rules mining is proposed, and the algorithm based on The interval concept lattice is used to control the adjustable precision rule mining model. Finally, the model analysis and case comparison verify that the model optimizes the mining cost and the control efficiency under the premise of improving the reliability of the rules.