文章摘要
煤矿瓦斯预测专家系统中基于粗集的知识获取方法
Knowledge acquisition approach based on rough sets theory in colliery gas forecast expert system
  
DOI:
中文关键词: 煤矿瓦斯突出预测  专家系统  粗糙集理论  知识获取
英文关键词: colliery gas forecast  expert system  rough sets theory  knowledge acquisition
基金项目:教育部人文社会科学研究青年基金项目(11YJC630195); 安徽省高校省级自然科学研究重点项目(KJ2012A076); 固体废物处理与环境安全教育部重点实验室开放基金资助(SWMES 2011-05)
作者单位
汪凌1,2 1. 安徽理工大学 经济管理学院,安徽 淮南 232001
2. 清华大学 固体废物处理与环境安全教育部重点实验室,北京 100084 
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中文摘要:
      提出了基于粗集理论的煤矿瓦斯预测专家系统知识获取方法.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.实例分析表明,粗糙集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.
英文摘要:
      An knowledge acquisition approach for colliery gas forecast expert system based on rough sets theory was proposed. This method firstly forecast samples were established between gas data and gas outburst intensity relationship; then algorithms of continuous attribute discretization, attribute reduction and rules extraction based on rough sets theory, and knowledge from lots of forecast samples was obtained automatically, and expert system knowledge database was constructed; Finally, based on reasoning machine, real-time data of gas forecast was realised. Example analysis results show that rough sets theory in coal mine forecast of gas expert system knowledge acquisition validity and practicability.
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