摘要
为加快量子遗传算法的参数更新速度,简化遗传操作步骤,提出了一种基于通用量子门的量子遗传算法(Quantum Genetic Algorithm with Universal Quantum Gate,UQGA)。该方法以通用量子门为逻辑计算单位,对染色体进行遗传操作。利用Hadamard门进行基础变换;通用量子门通过新的旋转角度函数,对各个基因位进行选择、变异操作;通过求解适应度函数,得到全局最优解;同时,算法经数学证明是收敛的。该算法应用到函数极值搜索和Iris数据集特征选择中。实验结果表明,UQGA具有较好的全局搜索和特征选择性能,尤其是在收敛速度、运算时间和分类准确率方面明显优于普通量子遗传算法和普通遗传算法。
To fasten the speed of parameters updating and simplified steps of genetic operation in quantum genetic algorithm,a novel algorithm of Quantum Genetic Algorithm with Universal Quantum Gates(UQGA)is proposed.In thismethod,firstly,universal quantum gate is the unit of logical computation for chromosomes.Then,Hadamard gate is usedfor basic operation.Each gene is selected and mutated with universal quantum gates through a novel function of rotationangle.Finally,by the solution of fitness function,the global optimal set is got.Meanwhile,the algorithm is mathematicallyproven to be convergent.The algorithm is applied in function extremum search and feature selection for Iris dataset.Theexperimental results indicate that,compared with CQGA and CGA,UQGA has better performance in global search andfeature selection,especially in convergence speed,execution time and classification accuracy.
作者
李胜
张培林
李兵
吴定海
胡浩
LI Sheng;ZHANG Peilin;LI Bing;WU Dinghai;HU Hao(Department Seventh, Ordnance Engineering College, Shijiazhuang 050003, China;Department Fourth, Ordnance Engineering College, Shijiazhuang 050003, China;Military Representation Department, Xianyang, Shaanxi 712099, China)
出处
《计算机工程与应用》
CSCD
北大核心
2017年第7期54-59,共6页
Computer Engineering and Applications
基金
国家自然科学基金(No.E51205405
No.E51305454)
关键词
量子计算
通用量子门
量子遗传算法
函数极值搜索
特征选择
quantum computation
universal quantum gates
Quantum Genetic Algorithm(QGA)
function extremum search
feature selection
