Network Traffic Anomaly Detection Based on ML-ESN for Power Metering System

Table 4

The parameters of ML-ESN experiment.

Parameters	Values
Input dimension number	5
Output dimension number	10
Reservoir number	3
Reservoir neurons number	1000
Reservoir activation fn.	Tanh
Output layer activation fn.	Sigmoid
Update rate	0.9
Random seed	50
Regularization rate