Table 3 Simulation parameters of proposed and existing implemented methods

GARU (proposed)

Bi_directional GRU

500

Bi_directional GRU

250

Attention layer

size of Bi_GRU

Dropout

0.2

Dense

100

Dropout

0.2

Dense

1

Bi_GRU

Bi_directional GRU

500

Bi_directional GRU

200

Dropout

0.2

Dense

100

Dropout

0.2

Dense

1

RNN

Embedding layer

input_dim = 100

GRU layer

256

Simple RNN layer

128

Dense

3

Bi_LSTM

Embedding layer

top_words = 10, n = 128

Bidirectional LSTM layer

64

Dropout

0.5

Dense

1

CNN

Input layer

69,769*1000

Convolution layer

Filter = 2, Kernel size = 2

Maxpooling layer

Pool size = 2

Flatten

Size of maxpool

Dense layer

1