李涛,郁美辰,陆正邦,林陈,张灿.基于关联规则挖掘的气象观测设备一致性检测算法[J].电子测量与仪器学报,2017,31(10):1568-1573
基于关联规则挖掘的气象观测设备一致性检测算法
Consistency detection algorithm for meteorological observation equipment based on association rules mining
  
DOI:10.13382/j.jemi.2017.10.006
中文关键词:  气象观测设备  一致性检测  兴趣度  关联规则
英文关键词:meteorological observation equipment  consistency detection  interest degree  association rules
基金项目:公益性行业(气象)科研专项(GYHY201306070)、江苏高校品牌专业建设工程(PPZY2015B134)、江苏省高等学校大学生创新创业训练计划项目(201610300031)资助
作者单位
李涛 南京信息工程大学电子与信息工程学院南京210044 
郁美辰 南京信息工程大学电子与信息工程学院南京210044 
陆正邦 南京信息工程大学电子与信息工程学院南京210044 
林陈 南京信息工程大学电子与信息工程学院南京210044 
张灿 南京信息工程大学电子与信息工程学院南京210044 
AuthorInstitution
Li Tao School of Electronic and Information Engineering, Nanjing University of Information Science & Technology,Nanjing 210044, China 
Yu Meichen School of Electronic and Information Engineering, Nanjing University of Information Science & Technology,Nanjing 210044, China 
Lu Zhengbang School of Electronic and Information Engineering, Nanjing University of Information Science & Technology,Nanjing 210044, China 
Lin Chen School of Electronic and Information Engineering, Nanjing University of Information Science & Technology,Nanjing 210044, China 
Zhang Can School of Electronic and Information Engineering, Nanjing University of Information Science & Technology,Nanjing 210044, China 
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中文摘要:
      为了保证气象观测设备采集数据的稳定性,从而需要对观测设备进行一致性检测。提出了一种基于兴趣度的关联规则的算法。并将该兴趣度关联规则挖掘算法应用于气象观测设备一致性检测上,可以形成关联规则气象观测设备一致性的模型。通过真实数据验证表明,该算法不仅能够挖掘出所有相关性很强的规则,同时与同类非Apriori类的算法相比,在时间性能上更加优越。通过该关联规则算法挖掘出所有关联项对形成范例库,利用规则匹配的方法对设备之间进行一致性检测,对算法实验优化,得到最优参数解,从而判定设备一致性。
英文摘要:
      In order to ensure the stability of data acquisition by meteorological observationequipment, the consistency detection of the observation equipment is needed. An algorithm of association rules based on interest degree is proposed in this paper. The interest association rule mining algorithm is applied to the consistency detection of meteorological observationequipment, and the consistency model of the meteorological observing equipment can be formed. Through real data validation, it shows that the algorithm can not only excavate all the very strong rules, but also better in the time performance compared with the algorithm of non Apriori class. Through this association rule algorithm, all the correlation items are excavated to form the example base, the rule matching method is used to detect the consistency between the equipment, the optimization of the algorithm is obtained, the optimum parameter solution is given, and the equipment consistency is determined.
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