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- W2372198075 abstract "Particle swarm optimization algorithm with self-adaptive constriction factor is proposed for the global optimization problems. The results of research is that a new constriction factor which is related to iteration steps is defined,with the increase of iteration steps the values of the constriction factor is aregradual decrease. The values of the constriction factor are the bigger in the former process of algorithm,and the capacity of searching global optimal solution is improved. On the contrary,The values of the constriction factor are the smaller and the capacity of local search is improved in the latter process of algorithm. Moreover,the crossing and selection operation of Differential Evolution(DE) is introduced to particle swarm optimization algorithm to improve the particle diversity. In the end,the algorithm is applied to two kinds of test problems ,and numerical experiment will verify the effectiveness and feasibility of this algorithm. The resuts have a certain reference value and instructive significance to solving the global optimization problems." @default.
- W2372198075 created "2016-06-24" @default.
- W2372198075 creator A5067840107 @default.
- W2372198075 date "2010-01-01" @default.
- W2372198075 modified "2023-09-23" @default.
- W2372198075 title "Particle swarm optimization algorithm with self-adaptive constriction factor" @default.
- W2372198075 hasPublicationYear "2010" @default.
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