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Description: 用量子粒子群算法解决ostu图像分割问题，达到了较好地效果-Quantum PSO ostu image segmentation solution, to achieve a better result
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Size: 1857 |
Author: wang zhang |
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Description:
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Size: 61440 |
Author: 陈厚合 |
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Description: QPSO（具有量子性质的PSO算法）算法优化聚类问题，其相关代码-QPSO (quantum nature of the PSO algorithm) to optimize the clustering problem, its associated code
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Size: 7168 |
Author: 由从哲 |
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Description: 用量子粒子群算法解决ostu图像分割问题，达到了较好地效果-Quantum PSO ostu image segmentation solution, to achieve a better result
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Size: 2048 |
Author: wang zhang |
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Description: 量子粒子群算法 mathlab,专门使用量子理论来提高粒子群算法的效率，经实验表明，运算准确性和效率有很大提升-Quantum Particle Swarm Optimization mathlab, specifically the use of quantum theory to improve the efficiency of particle swarm optimization, the experiments show that the accuracy and efficiency of computing has a great upgrade
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Author: jason |
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Description: 介绍了一种利用量子行为粒子群算法(QPSO)求解多峰函数优化问题的方法。为此，在
QPSO中引进一种物种形成策略，该方法根据群体微粒的相似度并行地分成子群体。每个子群体是
围绕一个群体种子而建立的。对每个子群体通过QPSO算法进行最优搜索。从而保证每个峰值都有
同等机会被找到，因此该方法具有良好的局部寻优特性。将基于物种形成的QPSO算法与粒子群算
法(PSO)对多峰优化问题的结果进行比较。对几个重要的测试函数进行仿真实验结果证明，基于物
种形成的QPSO算法可以尽可能多地找到峰值点，峰值收敛性能优于PS-A quantum behaved particle swarm optimization (QPSO) method for solving multimodal function optimization problems. For this reason, the introduction of a species in QPSO form a strategy, the method is based on the similarity of the groups of particles divided into sub-groups in parallel. Each sub-group is established around the seeds of a group. The QPSO algorithm optimal search for each sub-group. In order to ensure that each peak has the same opportunity to find, this method has good local optimization features. Will compare the results of multimodal optimization problems based on QPSO algorithm and particle swarm optimization (PSO) species formed. Simulation results prove that several important test function, based species formed QPSO algorithm can be as much as possible to find the peak point, the peak convergence outperforms PS
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Author: zhuifenger |
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Description: ：智能算法如粒子群算法已被应用于PID控制器的参数优化，以弥补传统优化方法容易产生振荡和较大超调量
的不足，但是粒子群算法存在易于早熟的缺点，在分析量子粒子群算法的基础上，提出了使用量子粒子群算法优化PID控
制器的参数。为了兼顾控制系统的各项性能指标，根据控制器的实际要求对各项指标进行加权作为算法的目标函数，对
PID控制器进行多目标寻优。通过2个传递函数实例，分别使用z—N、粒子群算法和量子粒子群算法进行了PID控制器
参数优化设计，并对结果进行了分析。-Abstract：Heuristics such as particle swarnl optimization is employed to enhance the capability of traditional techniques，
which is easy to produce surge and big overshoot，but PS0 may be trapped in the local optima of the objective and lead to poor performance．
This paper propesed the quantum-behaved particle 8wsl in optimization for the parameter optimization of PID controller．
A fitness function containing performance indexes Was defined and the algorithm Was used in multi-object optimization of PID controllers．
Two examples were given to illustrate the design procedure and exhibit the effectiveness of the proposed method via tomo
parison study with the existing Z—N and PSO approaches．
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Size: 380928 |
Author: dhskja |
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Description: 实现了 SVM 在医学图像分类中的应用，通过医学图像的实验结果验证了该方法的有效性。
对 SVM 算法进行了深入研究，结合量子行为的粒子群算法的优点，提出了一种量子行为的粒子群算法和 SVM 结合的混合分类模型，应用于医学图像的分类中。
深入研究了 K-means 算法，结合了无监督聚类和监督分类方法的优点，提出了一种 K-means 和 SVM 结合的混合分类模型，并应用于医学图像的分类中。
利用粒子群和量子行为的粒子群算法对 K-means 算法进行了改进，并将改进的K-means 算法与 SVM 算法结合形成全自动分类模型，并且把它应用于医学图像的分类中。
-SVM in the classification of medical image applications, medical images through the experimental results verify the effectiveness of the method. SVM algorithm conducted in-depth research, combined with the quantum behavior of the advantages of particle swarm optimization, PSO and SVM combined behavior of a quantum mixed classification model, applied to medical image classification. In-depth study of the K-means algorithm combines the advantages of unsupervised clustering and supervised classification method, propose a hybrid combination of a K-means and SVM classification model, and applied to the classification of medical images. Improved particle swarm algorithm using particle swarm and quantum behavior of the K-means algorithm, and improved K-means algorithm and SVM algorithm combined with the formation of a fully automatic classification model, and apply it to medical image classification.
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Author: 招伟杰 |
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Description: 基于物种形成的PSO算法（SQPSO），里面含有量子粒子的思想。主要参考Blackwell的论文。采用的动态环境是MPB函数---移动峰基准函数10个峰-PSO algorithm based on the formation of species (SQPSO), which contains the idea of quantum particles. Blackwell main reference papers. Using a dynamic environment is moving peak MPB function--- 10 peaks benchmark functions
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Size: 3072 |
Author: 周和 |
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Description: PSO算法，Quantum inspired PSO for the optimization of simultaneous recurrent neural networks as MIMO learning systems-PSO algorithm，Quantum inspired PSO for the optimization of simultaneous recurrent neural networks as MIMO learning systems
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Size: 1024 |
Author: 李泽 |
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Description: The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value.
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Author: ramin |
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Description: 有关蚁群算法的44篇优秀论文，包括蚁群算法、量子蚁群算法、蚁群算法与粒子群算法的混合算法等。-44 excellent papers about ant colony algorithm, ant colony algorithm, quantum ant colony algorithm, ant colony algorithm and the mixed algorithm of particle swarm optimization (pso) algorithm.
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Author: wang |
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Description: 将量子粒子群算法与群搜索算法进行融合，有效提高了算法的搜索效果。-Quantum particle swarm optimization (pso) algorithm with group search algorithm fusion, effectively improve the search results of the algorithm.
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Description: 针对单级多资源约束生产批量计划问题,提出了基于量子粒子群算法求解该问题的方法。此算法将量子强大的领域搜索能力和基本粒子群算法(PSO)通过跟踪极值更新粒子的功能-On a single stage production lot-sizing problem of resource constraints, based on quantum particle swarm algorithm is proposed to solve the problem.The algorithm to the field of quantum powerful search ability and basic particle swarm optimization (PSO) through the tracking function of extremum updating particles
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Size: 2048 |
Author: 张亿 |
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Description: A New Quantum-Inspired Binary PSO: Application
to Unit Commitment Problems for Power Systems
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Author: shrhiaa |
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Description: pso-pid量子粒子群算法qpso的matlab代码以及pid控制器在matlab中的仿真程序-Pso- pid quantum particle swarm optimization (qpso matlab code and pid controller in matlab simulation program
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Size: 12288 |
Author: zhouzhou |
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Description: 本人所写的基于量子行为优化的粒子群算法，很好的解决了粒子群算法易于陷入局部最优解的缺点-I wrote particle swarm optimization based on quantum-behaved, a good solution to the shortcomings of particle swarm algorithm is easy to fall into local optima
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Author: mikhansay |
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Description: 量子粒子群算法应用。对三个水听器的位置定位，在假设水听器位置已知情况下，以及其他方法估计得到的时延，通过量子粒子群算法计算，验证量子粒子群算法的计算精度。-Quantum particle swarm optimization application. Position location of the three hydrophones in the hydrophone position assumed known case, and other methods for estimating time delay obtained by calculating the quantum PSO QPSO verify the accuracy of the algorithm.
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Size: 1024 |
Author: 王过线 |
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Description: 基于量子的粒子群优化算法,该算法通过粒子群有量子的行为，提高了算法的寻优能力，增强了算法的全局搜索能力，有效的避免了“早熟”问题。(Quantum based particle swarm optimization algorithm.The algorithm improves the searching ability of the algorithm by quantum behavior of particle swarm, and enhances the global searching ability of the algorithm, and effectively avoids "premature" problem.)
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Author: 一云
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Description: 带交叉算子的量子粒子群优化算法~~~~~~~~~~(Quantum Particle Swarm Optimization with Crossover Operator)
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Author: dw dw dw dw |
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