Equipment Quality Information Mining Method Based on Improved Apriori Algorithm

نویسندگان

چکیده

Equipment quality-related data contains valuable information. Data mining technology seems to be an efficient method for extracting knowledge from large amounts of data. In this paper, a general equipment quality information based on association rule is proposed complex equipment. Due the shortcomings classical algorithms such as long running time and high memory consumption, candidate itemset generation process optimized, improved Apriori algorithm proposed. Taking five experimental sets object, performance tested using complexity spatial evaluation criteria. Comparative experiments show that had advantages. To further implement processing representation, matrix-based strong extraction was certain type example, simulation experiment conducted in article reliability test sets, some interesting obtained through mining, verifying effectiveness method. The research promising with respect improving scientific level support.

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ژورنال

عنوان ژورنال: Journal of Sensors

سال: 2023

ISSN: ['1687-725X', '1687-7268']

DOI: https://doi.org/10.1155/2023/2155590