Enhanced Memetic Algorithm-Based Extreme Learning Machine Model for Smart Grid Stability Prediction

Algorithm 1

	Let be the smart grid operational data, where is the instance of the smart grid operational feature value and is the status of the grid.
(1)	Randomly generate bias , to , and weight , to.
(2)	Calculate the hidden layer output function by using the selected activation function .
(3)	Compute the output weight matrix , which maximizes the objective function . Here, is the Moore–Penrose generalized inverse of the . .
	Perform the prediction by using on the data , is the learning rate. ,
	Predict the final class label as
	Return score of the prediction