基于GA‑RF的强对流天气下动态容量评估

Dynamic Capacity Evaluation in Strong Convective Weather Based on GA‑RF

容量评估是优化配置管制席位和空域规划的重要依据,为寻找天气特征与运行容量之间的动态关系,提出了基于遗传算法优化随机森林(GA‑RF)的强对流天气下动态容量评估模型。首先,根据不同天气影响量化方法提取空域容量影响指标;然后,采用随机森林特征重要性排序法进行特征选择与降维;最后,构建基于GA‑RF的强对流天气下动态容量评估模型。以北京05扇区为例进行验证,验证结果表明,该模型可在复杂的强对流天气下获取较高的容量评估精度。

Capacity evaluation is an important basis for optimizing the allocation of control seats and airspace planning.In order to find the dynamic relationship between weather characteristics and operating capacity,a dynamic capacity evaluation in strong convective weather based on the genetic algorithm optimization randon forest(GA-RF)is proposed.Firstly,airspace capacity impact indexs are estracted according to different weather impact quantification methods.Then,the random forest feature importance ranking method is used to select features and reduce dimensions.Finally,the dynamic capacity evaluation model in strong convective weather based on GA-RF is constructed.Taking Beijing 05 sector as an example,the verification results show that the model can obtain high capacity evaluation accuracy in complex strong convection weather.