A Weighted Association Rules Mining Algorithm with Fuzzy Quantitative Constraints

被引：0
|
作者：
Lu, Qibing [1 ]
Sheng, Buyun [1 ]
机构：
[1] Wuhan Univ Technol, Sch Mech Engn, Hubei Digital Mfg Key Lab, Wuhan 430000, Peoples R China
来源：
PROCEEDINGS OF 2013 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CLOUD COMPUTING COMPANION (ISCC-C) | 2014年
关键词：
data mining; association rules algorithm; weighted support; fuzzy association;
D O I：
10.1109/ISCC-C.2013.34
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Along with production process automation and development of new products, manufacturing information in large quantity, contains more dimensions, in order to mine useful information from the manufacturing database, monitor and control manufacturing process effectively. A weighted association rules mining algorithm with fuzzy quantitative constraints (FQC-wed Apriori algorithm) is proposed in this paper. First, find association rules after database mining. Then, mine fuzzy association rules with fuzzy query. Last, find frequent itemsets with the improved weighted association rules algorithm. Manufacturing process information can be mined and effectiveness of the mining algorithm can be evaluated. The algorithm is applied to manufacturing process information mining in discrete manufacturing industry.
引用
收藏
页码：481 / 487
页数：7
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