基于改进Apriori算法的气象数据质量控制研究

Research on Quality Control of Meteorological Data Based on Improved Apriori Algorithm

针对传统气象数据质量控制算法存在的不足,首先提出将Apriori关联规则挖掘算法用于气象数据中,通过Apriori算法挖掘出关联规则;其次分析了Apriori算法存在的不足,提出了一种改进的MC_Apriori算法,通过真实数据仿真表明,新算法在时间性能上更加优越;最后,在原数据的基础上植入部分错误数据,通过与规则库中的关联规则进行规则匹配,找出错误数据率达到93.3%。

In view of the shortcomings of traditional weather data quality control algorithms,firstly,it is proposed to apply Apriori association rule mining algorithm to weather data,and use Apriori algorithm to publish association rules.Secondly,it analyzes the shortcomings of the Apriori algorithm,and proposes an improved MC_Apriori algorithm.The simulation of real data shows that the improved algorithm is superior in time performance;Finally,part of the wrong data was implanted on the basis of the original data.By matching the rules with the association rules in the rule base,it was found that the wrong data rate reached 93.3%.