一种耦合LSTM算法和云模型的疫情传播风险预测模型
李照, 高惠瑛, 代晓奕, 孙海

An Epidemic Spread Risk Prediction Model Coupled with LSTM Algorithm and Cloud Model
LI Zhao, GAO Huiying, DAI Xiaoyi, SUN Hai
表6 云模型的计算参数矩阵
Tab. 6 Calculation parameter matrix of cloud model
指标 低风险 较低风险 中风险 较高风险 高风险
A1 (0.0005, 0.0003, 0.1) (0.0030, 0.0013, 0.1) (0.0065, 0.0010, 0.1) (0.0540, 0.0307, 0.1) (0.1100, 0.0067, 0.1)
B1 (146.42, 97.61, 0.1) (293.97, 0.76, 0.1) (296.08, 0.65, 0.1) (298.14, 0.72, 0.1) (300.15, 0.62, 0.1)
B2 (144.63, 96.42, 0.01) (290.35, 0.72, 0.01) (292.29, 0.57, 0.01) (294.10, 0.64, 0.01) (295.83, 0.52, 0.01)
B3 (0.0008, 0.0005, 0.1) (0.0020, 0.0002, 0.1) (0.0029, 0.0003, 0.1) (0.0041, 0.0004, 0.1) (0.005 9, 0.000 8, 0.1)
B4 (1 288 026, 858 684,0.1) (2 691 607, 77037, 0.1) (2 902 592, 63620, 0.1) (3120 919, 81 931, 0.1) (3 379 396, 90 387, 0.1)
C1 (0.1500, 0.1000, 0.01) (0.4000, 0.0667, 0.01) (0.6000, 0.0667, 0.01) (0.7500, 0.0333, 0.01) (0.850 0, 0.0333, 0.01)
D1 (0.5000, 0.3333, 0.01) (1.5000, 0.3333, 0.01) (2.5000, 0.3333, 0.01) (4.0000, 0.6667, 0.01) (6.000 0, 0.6667, 0.01)
D2 (0.4409, 0.2940, 0.01) (1.5724, 0.4603, 0.01) (3.1944, 0.6210, 0.01) (5.3173, 0.7942, 0.01） (8.2675, 1.1726, 0.01)