基于粗糙集的数据挖掘系统在安全决策中的应用

Application of Data Mining System Based on Rough Set in Safety Decision-making

我国许多大、中型煤矿都建立了通风安全监测系统、井下突水监控系统、井下煤与瓦斯突出监测系统等煤炭安全决策系统,这些系统中积累了大量的原始数据。如何将数据演变成可以科学决策的信息是煤矿安全生产要考虑的问题。粗糙集理论作为能够定量分析不确定和不完备信息与知识的方法,为数据挖掘提供了一种新的方法。为了更好地解决在决策表不完备和不一致情况下的推理和决策问题,提出了一种基于属性简约的缺省规则挖掘模型。最后设计出了基于粗糙集的数据挖掘系统,将其应用到井下工作面瓦斯涌出量数据挖掘分析中,取得了不错的效果。

The coal mine safety decision - making systems, such as ventilation safety monitoring system, underground water inrush mo- nitoring system, underground coal and gas outburst monitoring system, have been established in many large and medium - sized coal mines of our country. A large amount of original data had been accumulated in these systems. How to transform data into information for scientific decision was a problem need to consider for coal mine safety production. Rough set theory, as a method of quantitative a- nalysis of incomplete and uncertainty knowledge, provided a new method for data mining. In order to solve the problems of reasoning and decision - making in incomplete and imprecise decision tables, a kind of default rule mining model based on reduction extended concept lattice was proposed. Finally, data mining system based on rough set was designed, which was applied in data mining analysis of underground gas emission, and achieved good results.