考虑环境特征的无人机气象探测数据关联规则挖掘方法

针对无人机气象探测数据提取时效性较低、难以与实际数据关联的问题，研究考虑环境特征的无人机气象探测数据关联规则挖掘方法。基于机翼类型和发动机性能，确认最优气象探测环境，基于关联规则算法，建立无人机探测数据挖掘模型，对照高程变化规律，分析气象探测环境参数特征与无人机气象探测数据关联度，挖掘无人机气象探测数据。实验结果表明：以20 h的无人机气象探测时间为标准，在气象数据词条不断增长的基础上，本文方法能够将挖掘时间控制在4.8 s以内，并在相对湿度数据关联过程中，能够与实际数据较为接近，保证气象数据挖掘的时效性，具有实际应用价值。

Association Rules Mining Method for UAV Meteorological Data Considering Environment Characteristics

Aiming at the problem of low timeliness of UAV meteorological detection data extraction and difficult to associate with actual data, a method of mining association rules of UAV meteorological detection data considering environmental characteristics is studied. Based on the wing type and engine performance, confirm the optimal meteorological detection environment, establish the UAV detection data mining model based on the association rule algorithm, compare the elevation change law, analyze the correlation between the characteristics of meteorological detection environment parameters and UAV meteorological detection data, and mine UAV meteorological detection data. The experimental results show that: Taking the 20 h UAV meteorological detection time as the standard, on the basis of the continuous growth of meteorological data entries, this method can control the mining time within 4.8s, and in the process of relative humidity data association, it can be close to the actual data, ensure the timeliness of Meteorological data mining, and has practical application value.