针对传统量子进化算法用于搜索某些适应度函数时稳定性和精确性差的问题,在计算量子旋转角时引入内分泌激素调节规律,使得量子旋转角根据种群进化代数及个体适应度值自适应调整,提出了一种基于内分泌激素调节机制的量子进化算法.并用于Schaffer函数寻优和三维人脑图像分割.仿真实验结果表明,该算法不仅保留了传统量子进化算法收敛速度快的特点,而且提高了其精确性和稳定性.%Section 1 of the full paper explains our improved algorithm mentioned in the title. Its core consists of;" The traditional quantum evolutionary algorithm is sometimes unstable and inaccurate when it is used in searching the best solution of a fitness function. To solve this problem more effectly, the endocrine hormone regulation law was introduced into the quantum evolutionary algorithm when quantum rotation angles were calculated. The quantum rotation angles were self-adaptable to match the number of the population evolutionary generations and those of fitness values of solutions. "This algorithm was applied to the Schaffer function and 3D human brain image segmentation; the experimental results, presented in Tables 2 and 3, Figs. 3 and 4, and Figs. 7 through 9, and their analysis show preliminarily that the stability and the accuracy of the quantum evolutionary algorithm was indeed improved while the high-speed of convergence was maintained.
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