Research Article
Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms
Algorithm 1
New Model of PSO pseudocode.
() Given a population of , individuals. | () Initialize the population at random. | () Until a stop criteria is reached: | () if is not improved during then | () Perform a velocity resting, (7). | () end if | () if then | () Create new neighbourhoods. | () end if | () Modify inertia weight, (6). | () for each individual do | () Evaluates their fitness. | () end for | () for each individual do | () Update its best position . | () end for | () for each neighbourhood do | () Update the best individual . | () end for | () for each individual and each dimension: do | () Compute the velocity update equation , (11). | () Compute the current position . | () if then | () Apply crossover operator, (8) and (9). | () end if | () if then | () Apply mutation operator, (10). | () end if | () end for |
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