Research on Efficient Association Analysis Algorithm towards Production Process Data

Abstract:

Association analysis of the production process data (PPD) can be discoveried on the quality relevant parameters with great impact, however, it’s different from correlation analysis of other fields, Huge amount of data due to the production process, and the many parameters involved in the production process, the existing association analysis algorithms as they deal with inefficiency, can not meet the practical application. This paper proposes a new process for the industrial production of efficient data association algorithm-AprioriMask, after the actual production process of association analysis verification, AprioriMask algorithm has significant performance improvements to meet the industrial production process data for correlation analysis.

• Periodical: Applied Mechanics and Materials (Volumes 556-562)
• Pages: 3827-3830
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.556-562.3827
• Online since: May 2014
• Authors: Ming Hui Wang*, Wen Li Shang, Fu Cheng Pan
• Keywords: Apriori, Association Analysis, Production Process Data

References

[1] Zhang Yuhui. The Application Research of Data Mining and SPC in Manufacturing Quality Control [D]. Shanghai Jiaotong University, (2009).

[2] Han Jiawei．Kamber M．Data Mining：Condepts and Techniques．Fan Ming．Meng Xiaofeng. Translation．Beijing：China Machine Press：(2001).

[3] R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. In Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, pages 207-216, Washington, DC, May 26-28 (1993).

DOI: 10.1145/170036.170072

[4] Ashok Savasere; Edward Omiecinski; Shamkant B. Navathe, An Efficient Algorithm for Mining Association Rules in Large Databases, VLDB, 1995., p.432, 444.

[5] Chun Zhang; Dezan Xie; Ning Zhang; Honghui Li; Feng Liu, The improvement of Apriori algorithm and its application in fault analysis of CRH EMU, Service Operations, Logistics, and Informatics (SOLI), 2011 IEEE International Conference on , vol., no., p.543, 547, 10-12 July (2011).

DOI: 10.1109/soli.2011.5986620

[6] Xu Huizeng. Research methods of data mining association rules[J]. Science Technology and Engineering, 2012, 12(1): 60-63.

[7] Jong Soo Park; Ming-Syan Chen; Yu, P.S., Using a hash-based method with transaction trimming for mining association rules, Knowledge and Data Engineering, IEEE Transactions on , vol. 9, no. 5, p.813, 825, Sep/Oct (1997).

DOI: 10.1109/69.634757

[8] Tian Jiarui, Zhang Wenzheng etc. Correlation analysis of traffic alert information on backbone network [J]. Application Research of Computers, 2011, 28(1): 287-289.

[9] Li Qiang. Research on Correlation Analysis Algorithms in Data Mining [D]. Harbin Engineering University, (2010).