The invention relates to a flight emergency prediction method and apparatus based on an LSTM neural network. The method comprises the steps of obtaining sample data of historical accident flight records; preprocessing the sample data, then performing dimension reduction on the sample data by utilizing an MDDM algorithm, and mapping the sample data into a multi-dimensional vector; constructing a prediction data set by taking the multi-dimensional vector as a sample; dividing the prediction data set into a training set, a verification set and a test set, and training an LSTM neural network until the error of the LSTM neural network is lower than a threshold value and tends to be stable; and inputting the current flight data into the trained LSTM neural network to obtain the flight emergency probability. According to the invention, related data of historical flight emergencies are subjected to preprocessing, dimensionality reduction and feature extraction and are used as samples to train the LSTM neural network, so that various data in the flight process are automatically and comprehensively monitored, early warning is given out for the flight emergencies in time, and safe execution of flight tasks is guaranteed.
本发明涉及一种基于LSTM神经网络的飞行紧急事件预测方法及装置,其方法包括:获取历史出险飞行记录的样本数据;对样本数据中进行预处理,然后利用MDDM算法对其进行降维,并映射为多维向量;根据所述多维向量作为样本,构建预测数据集;将所述预测数据集划分为训练集、验证集、测试集,训练LSTM神经网络直至其误差低于阈值并趋于稳定;将当前飞行数据输入到所述训练好的LSTM神经网络,得到发生飞行紧急事件概率。本发明通过对历史飞行紧急事件的相关数据进行预处理、降维、特征提取并将作为样本训练LSTM神经网络,从而使得飞行过程中的各项数据都得到了自动化且全面的监控,并及时对飞行紧急事件发出预警,保障了飞行任务的安全执行。
Flight emergency prediction method and device based on LSTM neural network
一种基于LSTM神经网络的飞行紧急事件预测方法及装置
2021-04-09
Patent
Electronic Resource
Chinese
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