Bitmap-Base Association Rule Optimization Algorithm and Application in Equipment Fault Diagnosis

Abstract:

Article Preview

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)

Edited by:

Jian Gao

Pages:

1669-1672

DOI:

10.4028/www.scientific.net/AMR.308-310.1669

Citation:

Q. X. Zhu et al., "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

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.