多策略混合改进的海洋捕食者算法及其工程应用

为解决海洋捕食者算法(MPA)自适应能力有限、易陷入局部最优等问题,提出融合多策略改进的海洋捕食者算法(EMPA)。首先,在种群初始化阶段,采用精英反向学习策略初始化猎物种群,丰富种群的多样性。其次,在阶段更新过程中,设计出具有更强非线性收敛性的自适应惯性权重,控制捕食者在整个过程中的位置更新。在此基础之上,在等速比阶段,引入算术优化算子指导猎物搜索空间,平衡种群的全局勘探和局部开采。进一步,在海洋记忆存储阶段,采用t分布变异策略对猎物位置进行变异,增强个体在迭代后期跳出局部最优的能力。通过在8个测试函数上的算法性能测试及与著名算法的比较,验证了EMPA算法的优越性。最后,针对传统方法设计的断路器储能弹簧结构参数设置不合理、分断性能差等缺陷,应用EMPA对断路器储能弹簧进行优化设计,实验结果表明,EMPA算法的设计结果更加小型化、分断性能更优。

Comparison of Compositions and Structural Characterizations of Synthetic Nano-hydroxyapatite and Mineral Phase from Porcine Femoral Bone

In the paper, nano-hydroxyapatite was synthesized by hydrothermal treatment. The crystal morphology and compositions of the synthetic HA were investigated using TEM, IR, XRD and XPS techniques and were compared with those of porcine femoral bone apatite. The results showed that the synthetic HA is nanometer rod crystal similar to the bone apatite, and the average crystal sizes calculated by Scherrer equation for the four samples (HA dried at 80℃, unburned bone apatite, HA calcined at 750℃ and bone apatite calcined at 750℃) are 20.6, 21.7, 22.5 and 27.6nm, respectively. Moreover, the essential compositions for the synthetic HA and bone apatite are almost the same.