摘要
该文采用数据挖掘中的时间序列模式对流程企业中的实际运行数据进行分析,首先采用模糊理论对实际数据进行处理,找出偏离常规运行状态但未到报警界限的参数点并模糊化,然后采用时间窗对参数离散处理,划分时间间隔得到时间序列数据库。然后对传统的Apriori算法进行改进,提出了基于关联规则的时间序列分析算法并编程实现,起到了对设备故障预警监控的作用。
To monitor flowing industry's production,the large history database is analyzed by fuzzy theory and the exceptional equipment's parameters are found.The parameters in real-time database are scattered by time-window approach.A new time-interval sequential database is got by dealing with time intervals.In order to find time-interval rules,the conventional Apriori algorithm is modified and implemented in flowing industry.Then the models can monitor faults when the equipments circulating.
出处
《计算机工程与应用》
CSCD
北大核心
2005年第7期27-29,共3页
Computer Engineering and Applications
基金
国家863高技术研究发展计划项目(编号:2002AA412410)
