Aerial Vehicles follow a guided approach based on Latitude, Longitude and Altitude. This information can be used for calculating the status of maneuvering for the aerial vehicles along the line of trajectory. This is a binary classification problem and Machine Learning can be leveraged for solving such problem. In this paper we present a methodology for deriving maneuvering status and its prediction using Linear, Distance Metric, Discriminant Analysis and Boosting Ensemble supervised learning methods. We provide various metrics along the line in the results section that give condensed comparison of the appropriate algorithm for prediction of the maneuvering status.

翻译：航空飞行器采用以纬度、经度和高度为基础的指导方法。此信息可用于计算飞行器沿轨轨轨迹的机动状态。这是一个二进制分类问题,可用于解决此类问题。在本文件中,我们提出了一个计算机动状态及其预测的方法,使用线性、远程计量、差异分析和促进受监督的强化学习方法。我们在结果部分的一行中提供了各种衡量标准,对用于预测机动状态的适当算法进行了压缩比较。