Table 4 Summary of used variables.

From: Exploring the efficacy of GRU model in classifying the signal to noise ratio of microgrid model

Variable

Description

P(\(n\))

The probability density function for the noise (\(n\))

\(\pi \)

Pi which is approximately equal to 3.14159

\({\sigma }^{2}\)

The variance of the noise

\(e\)

Euler’s number

\({SNR}_{linear}\)

The Signal-to-Noise Ratio in linear scale

\({P}_{signal}\)

The power of the signal

\({P}_{noise}\)

The power of noise

\({SNR}_{dB}\)

The SNR is converted to decibels dB

\(log\)

Logarithm

CSV

Comma-separated values file

filename

String variable used to specify the path of the CSV file

PORT

String variable used to assign the port number for communication

BAUD_RATE

The maximum rate for transmitting bits per second

END_TIMEOUT

The timeout for sending data

RECV_TIMEOUT

The waiting time in seconds for receiving data

\({z}_{i}\)

The logit for class \(i\)

\(N\)

The total number of classes

\({r}_{t}\)

The reset gate at time \(t\)

\(\upsigma \)

The sigmoid function

\({W}_{r}\)

The weight associated with the rest gate

\({h}_{t-1}\)

The output of the previous hidden state at time \(t-1\)

\({x}_{t}\)

The input \(x\) at the current time \(t\)

\({b}_{r}\)

The bias term of rest gate

\({z}_{t}\)

The update gate at time t

\({W}_{z}\)

The weight associated with the update gate

\({b}_{z}\)

The bias term of the update gate

\({\overline{h} }_{t}\)

The candidate hidden state at time t

\({W}_{h}\)

The weight associated to the candidate hidden state

\({b}_{h}\)

The bias term of the candidate hidden state

\({h}_{t}\)

The final activation at time t