Meteorological Observation Equipment Consistency Testing Based on Association Rule Mining Algorithm

Abstract

In order to ensure the stability of the data collected by the meteorological observation equipment, it is necessary to conduct consistency detection on the observation equipment. This paper proposes an algorithm based on interest degree association rules. The interest association rule mining algorithm is applied to the consistency detection of meteorological observation equipment, and the consistency model of meteorological observation equipment of association rules can be formed. The verification of real data shows that the algorithm can not only mine all the rules with strong correlation, but also be superior in temporal performance compared with similar non-Apriori algorithms. Through association rule mining algorithm, all association items are extracted to form a case base. The rule matching method is used to detect the consistency between devices, and the algorithm is optimized experimentally, and the optimal parameter solution is obtained, which determines the device consistency.