A Weighted Association Rules Mining Algorithm with Fuzzy Quantitative Constraints

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 item sets 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.

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