基于神经网络的COVID-19数据分析与预测

Analysis and Prediction of COVID-19 Data Based on Neural Networks

文章针对新型冠状病毒(COVID-19)管控难以及疫情治理难等普遍性问题,对国内外疫情数据进行预处理并实现数据的可视化显示,然后通过时序分析方法中的趋势分析和突变分析识别,建立基于神经网络的数据分析模型——ANN模型和LSTM模型。通过训练模型展示出疫情相关结果,预测疫情发展趋势。其结果与实际趋势能够很好地对应起来,进一步验证了两种模型的有效性和实用性。

In view of the common problems such as the difficulty of COVID-19 management and control and the difficulty of epidemic management,this paper preprocesses the domestic and foreign epidemic data and realizes the visual display of the data.Then,through the trend analysis and muta-tion analysis identification in the time series analysis method,the data analysis model based on neural networks-ANN model and LSTM model are es-tablished.Display epidemic related results through training models and predict the development trend of the epidemic.The results correspond well with the actual trends,further verifying the effectiveness and practicali-ty of the two models.