摘要
针对航空安全自愿报告的特点,将关联规则挖掘算法中改进的Apriori算法应用于航空安全报告。提出用规则前后件约束的方法挖掘异常事件和事件原因之间的关联规则,不但限制冗余规则的生成,还进一步提高了挖掘的效率和精度。依据生成的频繁项集对引起航空事件的主要原因进行分析,总结了一些对提高民航安全水平有价值的决策信息。
According to the characteristics of aviation safety reports,association rules mining algorithm is applied to analyzing aviation safety reports,and association rules between the anomalies and causes of aviation incidents are analyzed using constraint-method of before and after pieces of rules.The algorithm not only limite the generation of redundant rules,but also further enhance the efficiency and accuracy of the excavation,and the causes of aviation incidents depending on found frequent item sets are analyzed.Finally,some valuable results are gained through above-mentioned analysis.
出处
《计算机工程与设计》
CSCD
北大核心
2011年第1期218-220,346,共4页
Computer Engineering and Design
基金
国家自然科学基金项目(60776806
60672174)
中国民航大学博士启动基金项目(06qd08s)
