摘要
本文主要研究如何运用关联规则来评价巷道瓦斯危险源的风险程度,作为分析煤矿事故危险源的补充.文章在云模型的基础上,针对煤矿安全监测数据的特点,提出一种基于云理论的属性空间软划分模型,然后在此基础上对Apriori算法进行了改进,提出适用于对煤矿安全监测数据进行关联规则挖掘的算法.最后通过实例测试,验证了改进算法的有效性.
Gas is the most important part in the safety of coal mine production. The research is mainly about how to apply the assoeiation rules to evaluate roadway,which can be the complement for the analysis of dangerous source. According to the charaeters of safety monitoring data in coal mine, we propose an attribute spatial soft-division model based on cloud theory. Then we use the model to improve the Apriori algorithm, and propose an algorithm that is suitable for associate rule mining of safety monitoring data. Finally, we test it with example, this can prove the effectiveness of the algorithm.
出处
《小型微型计算机系统》
CSCD
北大核心
2008年第9期1622-1626,共5页
Journal of Chinese Computer Systems
基金
国家自然科学基金项目(50674086)资助
江苏省科技项目(BS2006002)资助
关键词
云理论
关联规则
瓦斯危险源
APRIORI算法
cloud theory
association rules
coal mine gas danger parameters
Apriori algorithm
