自动站数据质量控制中关联规则挖掘的应用

为进一步提高自动气象站数据的业务可用性,提出了基于关联规则挖掘技术的自动气象站数据质量控制算法,以相对湿度与风向、风速观测要素变化间的关联关系为例,总结了自动气象站相关观测项目间可能存在的关联规则,进而指导建立适合不同地域、不同气候特征的专家知识规则库,用以完善自动气象站数据质量控制系统,为天气预报和气象服务提供更加精准的气象观测数据。文章还对关联规则专家知识库的可靠性进行了验证,具备了一定的实用价值。

Application of Association Rule Mining in AWS Data Quality Control System

In order to increase the availability of automatic weather station data, a data quality control algorithm for automatic weather stations based on association rules mining is proposed.Taking the relationship between relative humidity and wind direction and speed changes as the example, some possible association rules among observation items are summarized to guide the installation of the expert knowledge rule base that is suit for different areas and climate characteristics.The goal is to perfect the data quality control system for automatic weather stations and provide more accurate meteorological observation data for weather forecasts and meteorological service.The dependability of the expert knowledge rule base with certain practical value is verified.