摘要
针对机坪地面空调工况监测网络采集的数据量冗余引起的数据处理效率低的问题,提出一种基于矩阵压缩的Apriori改进算法。修改后Apriori算法改进Apriori拥有大量候选集和频繁扫描事务库低效问题,对构造矩阵里行和列中1的个数进行累加求和,对其和进行排序并删掉非频繁的向量,形成新的矩阵,对新矩阵依次进行累加、排序和删除,直到求出所有频繁项集。对改进算法进行性能分析并验证其有效性。
For the low efficiency problem of data processing caused by the amount of data redundancy of ground air condition monitoring network, the improved algorithm method with compressing matrix was proposed. The modified Apriori algorithm solved the low efficiency problems caused by large candidate sets and frequent scan transaction database by constructing arrays and giving a summation of the number 1 in the rows and columns. The new matrix was formed by sorting summation and deleting the infrequent rows and columns, and all frequent itemsets were obtained in circles. The performance analysis of improved algorithm verifies the optimization ability of the algorithm.
作者
曲睿
张天娇
QU Rui ZHANG Tian-jiao(School of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, Chin)
出处
《计算机工程与设计》
北大核心
2017年第8期2127-2131,共5页
Computer Engineering and Design
基金
中国民航局民航联合研究基金项目(U1433107)
中央高校基本科研业务中国民航大学专项基金项目(3122014D021)
中央高校基本科研业务费基金项目(Y16-08)
关键词
地面空调
监测网络
APRIORI算法
矩阵压缩
频繁项集
ground conditioning
monitoring network
Apriori algorithm
matrix compression
frequent itemsets
