基于关联规则的远洋舰船运行监控大数据挖掘方法

Large data mining method for ocean ship operation monitoring based on association rules

针对传统的远洋舰船运行监控大数据挖掘方法精准度低的情况,本文应用关联规则算法,对远洋舰船运行监控大数据挖掘方法进行设计。为了有效对舰船远行监控大数据挖掘,首先获取监控数据源,将数据存入到数据库中,在此基础上,对远洋舰船运行监控数据预处理,以此生成舰船运行监控大数据挖掘模型,完成了对运行监控大数据的挖掘,实验对比结果表明,本文设计的基于关联规则的远洋舰船运行监控大数据挖掘方法比传统的舰船运行监控大数据挖掘方法精准度高,具有一定的实际应用意义。

In view of the low precision of the traditional large data mining method for ocean-going ship operation monitoring,this paper designs a large data mining method for ocean-going ship operation monitoring by using association rule algorithm.In order to effectively mine the large data of warship remote monitoring,firstly,the monitoring data source is acquired and stored in the database.On this basis,the data of ocean-going warship operation monitoring is preprocessed to generate the large data mining model of warship operation monitoring,and the mining of the large data of operation monitoring is completed.The table of experimental results is compared.It is clear that the large data mining method of ocean-going ship operation monitoring based on association rules designed in this paper is more accurate than the traditional large data mining method of ship operation monitoring,and has certain practical application significance.