Table 2.

The optimal parameter settings of the baseline techniques.

Model	Parameter	Value
CNN	Convolution Layers	2
	Max-Pooling Layers	1
	Filter Size	(64,32)
	Kernel Size	3
	Pool Size	3
	Activation	ReLU
	Optimizer	Adam
	Learning Rate	0.0001
MLP	Layers	2
	Neurons	(64,64)
	Activation	ReLU
	Learning Rate	0.001
	Optimizer	Adam
	Batch Size	256
LSTM	Layers	2
	Neurons	(64,64)
	Activation	ReLU
	Learning Rate	0.001
	Optimizer	Adam
	Batch Size	128
GRU	Layers	2
	Neurons	(64,64)
	Activation	ReLU
	Learning Rate	0.001
	Optimizer	Adam
	Batch Size	128
BiLSTM	Layers	2
	Neurons	(64,64)
	Activation	ReLU
	Learning Rate	0.001
	Optimizer	Adam
	Batch Size	128
BiGRU	Layers	2
	Neurons	(64,64)
	Activation	ReLU
	Learning Rate	0.001
	Optimizer	Adam
	Batch Size	128
SVR	Kernel	Linear
	C	1.0
	Maximum Iterations	1000