量子进化

仿真实验对这两类图像使用相应的特征分别进行了基于量子进化RBF网络的图像识别。

Simulations of image recognition for both types of images were carried out using the appropriate features based on the quantum evolution RBF network .

量子进化和模拟退火的混合优化算法

Mixed Optimization Algorithm Based on Quantum Evolution and Simulate Anneal

量子进化算法及其在QoS组播路由和网络入侵检测中的应用

Quantum Evolutionary Algorithm and Its Application on QoS Multicast Routing and Network Intrusion Detection

基于量子进化算法的RNA序列-结构比对

RNA Sequence-structural Alignment Based on Quantum Evolutionary Algorithm

量子进化算法QEA（Quantum-InspiredEvolutionaryAlgorithm）将量子理论引入进化计算领域，是一种基于量子计算概念的进化策略算法。

Quantum-inspired evolutionary algorithm ( QEA ) is a kind of evolutionary strategy algorithms inspired by quantum computing .

本文的主要工作有：采用量子进化算法对RBF网络的参数及结构进行优化。

The main work of this paper is as follows : Quantum Evolutionary Algorithm is introduced into the optimization of parameters and structure of RBF network .

一种求解Flow-Shop调度问题的混合量子进化算法

Hybrid quantum inspired evolutionary algorithm for flow-shop scheduling problem

本文将量子进化算法用于RBF网络（径向基函数网络）的优化当中，并通过仿真验证了算法的有效性。

Quantum Evolutionary is introduced into the optimization of RBF network ( Radial Basis Function Network ) in this paper , simulation results show the effectiveness of the algorithm .

通过求解TSP问题库中的部分问题，表明改进的算法比经典的量子进化算法及免疫遗传算法具有更快的收敛速度和更好的全局寻优能力。

The computation results of problems from TSP database indicate that the performance of improved QEA is superior to that of the conventional QEA and the immune evolutionary algorithm .

文章将量子进化算法（QEA）和粒子群算法（PSO）互相结合，提出了两种混合量子进化算法。

Inspired by the idea of hybrid optimization algorithms , this paper proposes two hybrid Quantum Evolutionary Algorithms ( QEA ) based on combining QEA with Particle Swarm Optimization ( PSO ) .

量子进化算法（Quantum-InspiredEvolutionaryAlgorithm，QIEA）是一种以量子计算和进化算法结合的概率搜索方法，是进化算法家族中的后起之秀。

The quantum-inspired evolutionary algorithm ( QIEA ) is a kind of probability search method , which is combined the quantum computing and evolutionary algorithm . It is a rising star in the evolutionary algorithm family .

在研究进化算法的基础上，研究了一种量子进化规划算法，仿真结果表明该算法比采用高斯变异的传统进化规划算法的收敛速度快，并将该算法应用于FIR数字滤波器的优化设计；

The main research outcomes are as follows : 1 . Based on the research of evolutionary algorithms , a quantum-inspired evolutionary programming is proposed and simulations show that QEP is better than conventional EP , because of its rapid convergence and global search capability .

IEEE-RTS仿真算例表明改进的量子进化算法在求解检修计划优化问题时，相比量子进化算法和遗传算法具有种群进化速度更快、搜索能力更强的特点。

Using the data of IEEE-RTS , test simulations indicate that the improved quantum evolutionary algorithm has characters of evolving faster and stronger search ability than quantum evolutionary algorithm .

量子进化算法QEA实质是一种概率演化算法，而未使用进化算法中的变异，交叉等概念，因此会在某些问题陷入局部最优。

The Quantum Evolutionary algorithm QEA is a probabilistic algorithm , without the operations of crossover and mutation as in classical evolutionary algorithms , so it is limited by the local optimum problem in many applications .

量子进化算法QEA兼具量子计算与进化计算的优点，搜索能力和收敛速度均优于传统进化算法，近年来已成功应用于多个领域，但尚未见其在数据网格副本管理中的应用。

Quantum Evolutionary Algorithm ( QEA ) combines the advantages of both the quantum computing and evolutionary computing , and it has better search capability and convergence speeds compared with the traditional evolutionary algorithms . In recent years , QEA has been successfully used in many fields .

函数优化和0-k背包问题实验表明，与量子进化算法和传统遗传算法相比，概率进化算法在适用范围、搜索能力和收敛速度上有明显的优势。

The function optimization and 0-k knapsack problem experiments show that PEA has apparent superior in application area , searching capability and computation time compared with QEA and canonical genetic algorithm ( CGA ) .

本文在量子进化算法的基础上结合基于克隆选择学说的克隆算子，提出了改进的进化算法&量子克隆进化策略算法（QCES）。

Based on the combining of the quantum evolutionary algorithms ( QEA ) with the main mechanisms of clone , an improved evolutionary algorithm-quantum clonal evolutionary strategies ( QCES ) was proposed in this paper .

一种新量子进化算法及其在函数优化中的应用

Novel Quantum-inspired Evolutionary Algorithm and Its Application to Numerical Optimization Problems

基于学习的并行免疫量子进化算法及收敛性

Parallel Immune Quantum Evolutionary Algorithm Based on Learning Mechanism and Its Convergence

具有资源约束的项目调度问题中的量子进化算法

Quantum-inspired evolutionary algorithm for resources constrainted project scheduling problem

基于混合量子进化算法的流水车间调度方法研究与应用

Research and Application of Flow-Shop Scheduling Methods Based on Hybrid Quantum-Inspired Evolutionary Algorithm

基于量子进化算法的固井方案优化设计

Cementing plan optimization design based on quantum evolution algorithm

提出了量子进化算法在模拟演化电路中的应用。

Proposes the use of Quantum-inspired Evolutionary Algorithm ( QEA ) in AEC .

量子进化算法和免疫算法的比较研究

Comparative study of quantum evolutionary algorithm and immune algorithm

有能力约束车辆路径问题的量子进化算法

Quantum evolutionary algorithm for capacitated vehicle routing problem

基于量子进化算法的机器人联盟编组优化研究

Multi-Robot Coalition Formation Based on Quantum Evolutionary Algorithm

混合量子进化算法及其应用

Hybrid Quantum Evolutionary Algorithms and its Application

该方法将量子进化聚类算法应用于图像分割。

In this algorithm , we introduced Quantum-Inspired Evolutionary Clustering Algorithm to the image segmentation .

概率门量子进化算法

The Door Probability gate quantum evolution algorithm

一种实数编码量子进化算法及其收敛性

Real-coded quantum-inspired evolutionary algorithm and its convergence