Abstract
At present, many scholars have conducted extensive research on parameter design in particle swarm optimization algorithms and have achieved many results. The particle swarm algorithm is easy to fall into the local optimum, so the paper modifies the particle swarm parameters to improve the algorithm's performance. To further improve the algorithm, this paper proposes a combination of flower pollination and particle swarm algorithm. The comparison of the optimization accuracy and the convergence speed on the four test functions proves the superiority of the flower pollination and particle swarm algorithm.
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