微粒群多元最优信息的模糊自适应规划算法

Fuzzy Adaptive Programming Algorithm Based on Particle Swarm Multi-optimum Information

  • 摘要: 在静态的微粒群多元最优信息规划模式的基础上,提出了微粒群多元最优信息的模糊自适应规划算法.该算法将模糊逻辑引入微粒群多元最优分布状态的动态规划,以实现多元最优信息间规划比例在寻优过程中的自适应调节,从而能够更大程度地改善其总体寻优性能.以最优和次最优分布信息的规划为例,构造了一种基于单变量两维状态输入模糊控制结构的微粒群模糊自适应规划引导器,并加以仿真计算.

     

    Abstract: Fuzzy adaptive programming algorithm based on particle swarm multi-optimum is proposed on the basis of the static particle swarm multi-optimum information programming mode. Fuzzy logic is introduced into the process of multi-optimum distribution state dynamic programming, so that the proportion factor of multi-optimum programming can be dynamically adjusted in the optimization process, and therefore its performance can be improved greatly. A kind of particle swarm adaptive programming algorithm based on single-variable and two-dimension-input fuzzy control structure of optimum and sub-optimum distribution information is put forward and simulated.

     

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