A Newly Self-Adaptive Strategy for the PSO

Particle swarm optimization (PSO) is a kind of random optimization algorithm based on the swarm intelligence. It has been used in many optimum problems and Its behave is better. This paper presents newly nonlinear self-adaptive parameters for the PSO (PSO-NL) and we compare it with the linear self-adaptive parameters for the PSO (PSO-TVAC). The experimental results show that the PSO-NL has a fast convergence and is feasible.

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