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。
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).
出处
《计算机工程》
CAS
CSCD
2013年第1期208-212,共5页
Computer Engineering
基金
广州市科技计划基金资助项目(12C22111580)
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
quantum computation
optimization algorithm
Quantum Genetic Algorithm(QGA)
oral implant localization
search space
CT medical data