Research on DUAL-ADGAN Model for Anomaly Detection Method in Time-Series Data

Algorithm 1

DUAL-ADGAN training network model pseudocode.

(1)	Function training network ;
	Input: Time series data sliced by sliding window x, Noise vector z
	Output: The trained WGAN generator , Fence-GAN discriminator , and predictor P
(2)	If model is WGAN:
(3)	For epochs do
(4)	Feed the noise vector z into the generator to generate the data
(5)	Feed the generated data and the real data x into the discriminator
(6)	Training and with WGAN-GP loss function
(7)	Return
(8)	If model is Fence-GAN:
(9)	For epochs do
(10)	Feed the noise vector z into the generator to generate the data
(11)	Feed the generated data and the real data x into the discriminator
(12)	Training and with Fence-GAN loss function
(13)	Return
(14)	If model is Predictor:
(15)	For epochs do
(16)	Preprocess the training data x into that matches the RNN input
(17)	Train the RNN network
(18)	Return P
(19)	end