Interval Short-Term Traffic Flow Prediction Method Based on CEEMDAN-SE Nosie Reduction and LSTM Optimized by GWO

Table 4

The result of different models.

Model	SSE	MAE	MSE	RMSE	MAPE
BP	11226551	93.60002	19524.4368	139.72987	0.16351147	0.926
LSTM	9756640	79.9905	16938.607	130.1484	0.1513894	0.936
GWO-LSTM	3560689	43.4375	6181.7526	78.6241	0.112324	0.977
CEEMDAN-SE-GWO-LSTM	1244319	37.3297	2160.2774	46.4788	0.106236	0.992