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.
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