基于Kalman滤波的Helmholtz机进化算法
Helmholtz Machine Evolutionary Algorithm Based on Kalman Filter
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摘要: 根据信息融合的思想，提出了基于Kalman滤波的Helmholtz进化算法(KFHMEA)。在KFHMEA中，首先将种群分成若干子种群，各子种群独立使用Helmholtz机来估计其状态，然后用Kalman滤波器把这些状态信息相融合，并将融合后的信息反馈到各子种群中。仿真实验表明，这种Kalman融合机制能够大大增强原有算法的稳定性和全局搜索能力，从而提高了算法的整体性能。Abstract: On the basis of information fusion, an Evolutionary Algorithm based on Helrnholtz Machine and Kalman Filter (KFHMEA) is proposed. In KFHMEA, the population is divided into several sub-populations and Helmholtz machine is used to estimate the state of each sub-population. Then the information of these states is fused using a Kalman filter, and the fused information is feed back to the sub-populations. Experimental results demonstrate that KFHMEA outperforms HMEA in the stability and global search ability.
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