Paper Title:
Bitmap-Base Association Rule Optimization Algorithm and Application in Equipment Fault Diagnosis
  Abstract

The Apriori algorithm needs to continue scanning the database and may provide mass candidate itemsets in fault diagnosis process which causes the mining speed too slow and the computer memory too large. According to these weaknesses this paper presents the bitmap-base association rule optimization algorithm (BARO). The BARO improves the data structure to reduce the scanning frequency of database and compresses the matrix to reduce the quantity of candidate itemsets in order to improve the speed of equipment fault diagnosis. It proves that BARO is superior to Apriori algorithm in equipment fault diagnosis of efficiency and mining speed by a concrete example.

  Info
Periodical
Advanced Materials Research (Volumes 308-310)
Chapter
Reverse Engineering
Edited by
Jian Gao
Pages
1669-1672
DOI
10.4028/www.scientific.net/AMR.308-310.1669
Citation
Q. X. Zhu, L. Zhang, J. Liu, P. S. Jiao, H. H. Hao, "Bitmap-Base Association Rule Optimization Algorithm and Application in Equipment Fault Diagnosis", Advanced Materials Research, Vols. 308-310, pp. 1669-1672, 2011
Online since
August 2011
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Price
$32.00
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