A “Tuned” Mask Learnt Approach Based on Gravitational Search Algorithm

Pseudocode 1

Pseudocode of GSA.

Begin

Generate initial population with N objects

While (The current iteration t < The maximum iteration T)

Compute the fitness value of each object by objective functions

Update the gravitational variable , and and of the population

Calculate the active gravitational mass , the passive gravitational mass , the inertial mass and the acceleration

for each object

Update velocity and position of each object by using (6)

If (The fitness value of current position is better)

Replace the object by the new position

End if

End while

Post process results and visualization

End