A Hybrid Model for Short-Term Traffic Flow Prediction Based on Variational Mode Decomposition, Wavelet Threshold Denoising, and Long Short-Term Memory Neural Network

Table 3

Parameter configuration of different models.

Model	Primary parameter	Setting value
ARIMA	p	2
	d	1
	q	4
EEMD	Added white noise	0.2
	The ensemble number	1000
LSTM	Learning rate	0.005
	The number of training epochs	250
	Number of hidden units	288
BiLSTM	Learning rate	0.005
	The number of training epochs	50
	Number of hidden units	32
ANN	Learning rate	0.005
	The number of training epochs	250
	Number of hidden units	288