实现了两种方法都是基于SEIRD模型的。
SEIRD-exp-decay：主要使用SEIRD模型，用梯度更新的方法学习其中的参数beta，gamma，alpha，theta，然后通过指数衰减的方法预测beta等参数的变化。
SEIRD-ARIMA：主要使用SEIRD模型，用梯度更新的方法学习其中的参数beta，gamma，alpha，theta，然后通过arima的方法预测beta等参数的变化。
基于2020-2-17号公布的数据
| 湖北 | 武汉 | 深圳 | 全国 | 非湖北 | |
|---|---|---|---|---|---|
| SEIRD-exp-decay | 03-05 | 03-12 | 02-08 | 02-20 | 02-13 |
| SEIRD-ARIMA | 03-03 | 02-24 | 02-08 | 无法预测 | 02-13 |
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