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针对AEA算法的收敛稳定度不高、易早熟等问题,给出一种融合人工蜂群(ABC)算法的改进AEA算法SAEA算法。在达到一定的优化程度时,根据人工蜂群算法的思想,按概率选择个体,并对所选择个体进行有限次的优化更新。通过与ABC和AEA算法对22个标准测试函数试验结果进行比较,以及对超临界水氧化动态参数的估计表明,提出的混合算法具有良好的收敛性以及全局优化性能。该算法既保证了在寻优过程中的收敛性,确保种群向着目标方向进化,也增加了种群的多样性,避免过早收敛。
AEA algorithm SAEA algorithm is proposed to improve the AEA algorithm, which is based on ABC algorithm. When reaching a certain degree of optimization, according to the idea of artificial bee colony algorithm, individuals are selected according to probability, and the selected individuals are optimized and updated for a limited time. The comparison between 22 standard test functions and ABC and AEA algorithms, as well as the estimation of dynamic parameters of supercritical water oxidation show that the proposed hybrid algorithm has good convergence and global optimization performance. The algorithm not only guarantees the convergence in the optimization process, but also ensures that the population evolves toward the target. It also increases the diversity of the population and avoids premature convergence.