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Proceedings of the 2010 International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2010)

By
International Association of Computer Science and Information Technology (IACSIT)
International Association of Computer Science and Information Technology (IACSIT)
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ISBN:
9780791859544
No. of Pages:
590
Publisher:
ASME Press
Publication date:
2010

The premise of Apriori algorithm is that the frequency and significance of each item in the database are equal or similar, but in the actual practice of fault diagnosis it's not the case. This paper improved it on the basis of Apriori algorithm, utilizing multiple minimum supports to solve the mining of non-frequent item in equipment fault diagnosis; meanwhile a CCWMMS Algorithm based on “credit component values” is proposed, which focus on the item's inconsistent degree of significance in the actual application. This paper also proved this algorithm's exactness and validity in fault diagnosis by actual examples.

Abstract
Key Words
1. Introduction
2. Association Rules And Apriori Algorithm
3. Multiple Minimum Supports Association Rules Algorithm
4. Weighted Multiple Minimum Supports Association Rules Algorithm
5. Conclusions
References
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