摘要： 口腔种植体设计方案的制定时间较长、智能程度不高，口腔医学数据信息量较大。为此，对种植体模型进行研究，提出一种改进的量子遗传算法。把种群细分为不同的特征群体，各特征群体实施自适应调整进化步长的量子旋转门操作，以及个体间信息交流的交叉操作。实验结果表明，与经典的遗传算法以及Bloch量子遗传算法相比，该算法能有效地优化种植体定位参数，搜索能力和收敛性能较好。
关键词:
量子计算,
优化算法,
量子遗传算法,
口腔种植体定位,
搜索空间,
CT医学数据
Abstract: According to the preparations of oral implant, hard work and low intelligence, an improved Quantum Genetic Algorithm(QGA) is proposed with the information of the dental medical data considered. With the implant localization model studied, this algorithm divides the population to several groups, which respectively takes self-adaptive evolution and communicative crossover operator. Experimental results show that this algorithm can effectively optimize implant positioning parameters, search ability and convergence performance is good compared with the Genetic Algorithm(GA) and Bloch Quantum Genetic Algorithm (BQGA).
Key words:
quantum computation,
optimization algorithm,
Quantum Genetic Algorithm(QGA),
oral implant localization,
search space,
CT medical data
中图分类号:
黄俊华, 唐平, 陈松龄, 江小平, 梁英蓬. 量子遗传算法在口腔种植定位中的研究与应用[J]. 计算机工程, 2013, 39(1): 208-212.
HUANG Dun-Hua, TANG Beng, CHEN Song-Ling, JIANG Xiao-Beng, LIANG Yang-Peng. Research and Application of Quantum Genetic Algorithm in Oral Implant Localization[J]. Computer Engineering, 2013, 39(1): 208-212.