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