量子遗传算法,quantum genetic algorithm
1)quantum genetic algorithm量子遗传算法
1.Converse solution of oil recovery ratio based on process neural network and quantum genetic algorithm;基于过程神经网络和量子遗传算法的油藏采收率参量逆向求解
2.A method of infrared image segmentation based on quantum genetic algorithm;一种基于量子遗传算法的红外图像分割方法
3.Active noise control method based on a new quantum genetic algorithm;基于改进量子遗传算法的有源噪声控制方法
英文短句/例句

1.Using Quantum Genetic Algorithm to Improve BP Learning Algorithm利用量子遗传算法改进BP学习算法
2.Research on Improved Quantum Genetic Algorithm to Solving Nonlinear Equation Group改进量子遗传算法求解非线性方程组
3.Optimization of filter parameters based on quantum genetic algorithm基于量子遗传算法的滤波器参数优化
4.Wireless Sensor Optimization Algorithm Based on QGA基于量子遗传算法的无线传感器网络节点定位算法研究
5.The Research on Intelligent Scheduling of Production Planning Based on Quantum Genetic Algorithm;基于量子遗传算法的生产计划智能调度研究
6.Algorithm of Bayesian Network Structural Learning Based on Quantum Genetic;基于量子遗传算法的贝叶斯网络结构学习
7.Reactive Power Optimization of Power System Based on the Quantum Genetic Algorithm;基于量子遗传算法的电力系统无功优化
8.Path Planning Based on Quantum Genetic Algorithm for Soccer Robot基于量子遗传算法的足球机器人路径规划研究
9.Reactive Power Optimization Based on Improved Quantum-Inspired Genetic Algorithm基于改进量子遗传算法的电力系统无功优化
10.The OFDM Adaptive Modulation Based on Quantum Genetic Algorithm基于量子遗传算法的OFDM自适应调制技术
11.A Solution About Quantum Genetic Algorithm to the Allocation of Radio Spectrum Cognitive一种解决认知无线电频谱分配的量子遗传算法
12.A Quantum Genetic Algorithm for Shortest Path Routing Problem一种求解最短路径路由问题的量子遗传算法
13.Power and area optimization of XOR/AND circuits based on quantum genetic algorithm基于量子遗传算法的XOR/AND电路功耗和面积优化
14.Optimal Knowledge Distribution Based on the Quantum Genetic Algorithm基于量子遗传算法的知识分布优化研究
15.Training method of process neural networks based on hybrid quantum genetic algorithm基于混合量子遗传算法的过程神经元网络训练
16.Application of improved quantum genetic algorithm in PID parameter tuning改进量子遗传算法在PID参数整定中应用
17.Training of process neural networks based on improved quantum genetic algorithm基于改进量子遗传算法的过程神经元网络训练
18.Quantum-inspired Genetic Algorithm with Local Search and Its Applications in Reactive Power Optimization局部搜索量子遗传算法及其无功优化应用
相关短句/例句

Quantum Genetic Algorithm(QGA)量子遗传算法
1.The development of Quantum Genetic Algorithm(QGA) was researched.研究了量子遗传算法(QGA)的发展现状,运用量子遗传算法来解决物流管理系统中的成本问题,在应用程序中进行资源控制,设计了安全认证模式,并以每个人的身份进行系统权限的分配,进行了与企业运营成本有关的优化,包括装配车优化等。
2.By analyzing the current status of campus network and grid technologies, this paper presents job scheduling model and designs a job scheduling method based on Quantum Genetic Algorithm(QGA) in campus grid.通过对校园网现状和网格技术的分析,该文提出校园网格作业调度模型,设计并实现了基于量子遗传算法的作业调度方法。
3.A Quantum Genetic Algorithm(QGA) with repair function was proposed in this paper.提出了一种带修复函数的量子遗传算法来求解背包问题。
3)QGA量子遗传算法
1.This paper first proposes a QoS routing algorithm based on quantum genetic algorithm(QGA),whereby the multi-constraint QoS routing problems can be treated,including constraints such as bandwidth,delay,packet loss rates and least-cost and so on.提出了一种基于量子遗传算法解决多约束QoS路由问题的算法,详细讨论了该算法用于解决包含带宽、延时、包丢失率和最小花费等约束条件在内的多约束QoS路由问题,给出了算法实现的方法和具体流程。
2.This paper proposes a multicast QoS routing algorithm based on quantum genetic algorithm(QGA).提出了一种基于量子遗传算法QGA(quantum genetic algorithm)解决多播QoS(quality of service)路由问题的算法。
3.Quantum genetic algorithm(QGA) is a novel algorithm called probability evolutionary algorithm.还介绍了量子遗传算法,它是一种基于量子计算概念的智能算法,用量子比特为基本信息位编码染色体,用基于量子概率门的量子变异实现个体进化,其收敛速度和全局寻优能力优于传统进化算法。
4)genetic quantum algorithm遗传量子算法
1.Multiuser detection based on a clonal genetic quantum algorithm;基于克隆遗传量子算法的多用户检测
2.Brief Analysis Contrast Between Genetic Quantum Algorithm and Genetic Algorithms in Resolving Extremal Problem of the Function;浅析遗传量子算法与遗传算法在函数极值问题中的比较法
3.the Application of Genetic Quantum Algorithm on Under-constraint and Over-constraint of Geometric Constraint Solving;遗传量子算法在欠约束和过约束的几何约束求解问题中的应用
5)new quantum genetic algorithm新量子遗传算法
6)Quantum-Inspired Genetic Algorithm (QIGA)量子遗传算法(QIGA)
延伸阅读

数值遗传算法分子式:CAS号:性质:基于自然界生物进化机制的一种全局最优化方法。在遗传算法中,被研究体系的响应曲面看作为一个群体,响应曲面上的每一个点作为群体中的一个个体,个体用多维向量或矩阵来描述,组成矩阵的和向量的参数(元素)相应于生物中组成染色体的基因。染色体用固定长度的二进制位串(bit string)表示。通过交换(染色体基因交换)、突变(改变染色体基因)等遗传操作,在参数的一定范围内进行随机搜索,不断改善数据结构,构造出不同的向量,相当于得到了被研究问题的不同的解(一个个体相当于一个解)。目标函数较优的点被保留,较差的点被淘汰,最后达到全局最优化。