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Guaranteed by the indentation factor, the improved PSO algorithm can keep the iteration particles in feasible region.
通过引入缩进因子，改进P SO算法，使粒子在迭代过程中保持在可行域内。
The simulation results show that the improved PSO algorithm can solve the high-dimensional numerical optimization problem effectively.
实验结果表明该改进微粒群算法可以有效地解决高维数值优化问题。
For improving the predicting results, two improved PSO algorithm are presented also in this paper: Velocity Mutation PSO and hybrid PSO.
在此基础上，进一步提出了混合粒子群算法和速度变异粒子群算法两种改进算法提高优化性能。
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