Research Article
A Novel Multimean Particle Swarm Optimization Algorithm for Nonlinear Continuous Optimization: Application to Feed-Forward Neural Network Training
Algorithm 2
The pseudocode of the proposed MMPSO algorithm.
Initialize all particles of all swarms with randomly generated position and velocity | Repeat | For each swarm | For each particle in the swarm | Calculate the fitness function | Update the local best of positions | Update the global best position of the swarm | End for | Update the best position of all swarms | End for | For each swarm | For each particle in the swarm | Update the velocity and the position of the particle according to equations (6) and (5) | End for | End for | Until (Stopping criteria met) |
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