煤矿瓦斯预测专家系统中基于粗集的知识获取方法

针对现有煤矿瓦斯预测专家系统因没有新知识获取措施及知识自更新功能而预测效果不佳的问题,提出了基于粗集的知识获取方法。该方法首先建立瓦斯数据与瓦斯突出强度之间关系的预测样本集;然后运用粗糙集的连续属性离散化、属性约简以及规则提取算法,从大量的预测样本集中自动获取预测知识,并将预测知识存储于专家系统知识库中;最后基于推理机实现煤矿瓦斯突出的实时预测。实例分析验证了该方法在煤矿瓦斯突出预测专家系统知识获取中的有效性和实用性。

Knowledge acquisition approach based on rough sets theory for gas forecast expert system of coal mine

For problem of poor forecast effect of existing gas forecast expert system of coal mine because of no new knowledge acquisition measures and self-renewal function for knowledge,a knowledge acquisition approach based on rough sets theory was proposed.The method firstly establishes forecast samples of relationship between gas data and gas outburst intensity;then uses algorithms of continuous attribute discretization,attribute reduction and rules extraction based on rough sets theory to obtain forecast knowledge from lots of forecast samples,and stores the knowledge in knowledge database of expert system;finally,realizes real-time gas forecast based on reasoning machine.Example analysis result verifies effectiveness and practicality of rough set method applied in knowledge acquisition of gas forecast expert system of coal mine.