民用航空安全风险预测模型的研究

Research on Civil Aviation Safety Risk Prediction Model

为进一步提升民用航空安全风险预测能力水平,本文以长短期记忆(LSTM)的典型BP神经网络为基础,设计与优化其具体参数和算法流程,最终搭建基于双向LSTM-BP的民用航空安全风险预测模型,并测试其应用效果。测试结果显示,该模型在准确率的优势相对较为突出,证明该模型的设计取得了初步成功,具有一定的应用价值。

In order to further improve the ability of civil aviation safety risk prediction,this paper is based on the typical BP neural network with long-term and short-term memory(LSTM),the specific parameters and algorithm flow are designed and optimized.Finally,a civil aviation safety risk prediction model based on bidirectional LSTM-BP is established,and its application effect is tested.The test results show that the advantage of the model in accuracy is relatively prominent,which proves that the design of the model has achieved initial success and has certain application value.