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Description: qpso量子粒子群
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Size: 716 |
Author: lorexiao |
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Description: 全局收敛的PSO算法,可用于智能运算开发-Global convergence of the PSO algorithm can be used for the development of intelligent computing
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Size: 3072 |
Author: gao |
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Description: qpso算法解决电力系统最优化问题，例子是40个节点的大规模问题-qpso algorithm to solve power system optimization problems, for example, is a 40-node large-scale problems
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Size: 3072 |
Author: Mei Juan |
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Description: 量子粒子群优化算法，采用matlab编程，可实现快速优化多维函数，不易陷入局部最优值。-Quantum particle swarm optimization algorithm, using matlab programming, can be optimized for fast multi-dimensional functions, not easily trapped into local optimal values.
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Size: 1024 |
Author: 李志远 |
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Description: 本程序用量子行为的粒子群算法训练支持向量机，并用IRIS数据验证了该方法的有效性-This procedure acts with quantum particle swarm optimization training support vector machines, and IRIS data to verify the effectiveness of the method
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Size: 13312 |
Author: 李慧 |
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Description: K-MEANS聚类算法，以及PSO和QPSO算法改进K-MEANS算法，breastcancer数据验证了该分类模型的有效性-K-MEANS clustering algorithm, and the PSO algorithm and QPSO to improve K-MEANS algorithm, breastcancer data verified the validity of the classification model
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Size: 43008 |
Author: 李慧 |
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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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Size: 4096 |
Author: jason |
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Description: qpso的全局搜索性能远比基本的pso好，而且速度快。-qpso overall search performance than the basic PSO good, and fast.
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Size: 1024 |
Author: zhanlan |
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Description: 在网络异常检测中,为了提高对异常状态的检测率，降低对正常状态的误判率,本文提出一种基于量子粒子群优化算法训练小波神经网络进行网络异常检测的新方法。利用量子粒子群优化算法(QPSO)训练小波神经网络,将小波神经网络(WNN)中的参数组合作为优化算法中的一个粒子,在全局空间中搜索具有最优适应值的参数向量。- In order to improve the detection rate for anomaly state and reduce the false positive rate for normal state in the network anomaly detection, a novel method of network anomaly detection based on constructing wavelet neural network (WNN) using quantum-behaved particle swarm optimization (QPSO) algorithm was proposed. The WNN was trained by QPSO.
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Size: 1024 |
Author: liang |
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Description: QPSO算法的MATLAB源码，给需要的人，希望斑竹给加点技术分-MATLAB algorithm QPSO source, give the necessary people, hoping to add points Chiloscyllium technical sub-
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Size: 8192 |
Author: 老苗 |
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Description: 许多的PSO优化算法，包括BPSO、HybridPSO、QPSO、SPSO等等。-Many of the PSO optimization algorithms, including BPSO, HybridPSO QPSO, SPSO, etc.
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Size: 14336 |
Author: |
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Description: 自编的量子粒子群算法，基于C++，供学习者参考-Own quantum particle swarm optimization, based on the C++, for learner reference
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Size: 126976 |
Author: zangtianlei |
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Description: Online UAV path planning including online planning schedule, splane smoothing algorithm and QPSO algorithm
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Size: 6144 |
Author: James |
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Description: 量子粒子群算法的matlab实现，有程序说明-Quantum particle swarm optimization algorithm matlab implementation, there is description of the procedures
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Size: 1024 |
Author: logor |
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Description: k-中心与qpso算法的结合，从文档中读取对象数据，没有维限制。需要设定类别数，先由k-中心计算出各类中心，然后由qpso优化，得到聚类结果，并保存聚类信息。-algorithm for k-medians and qpso combination of object data read from the document, there is no dimension restrictions. Need to set the number of categories, first calculate the k-medians types of center, and then optimized by qpso obtained clustering results, and save the clustering of information.
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Size: 2048 |
Author: 飞 |
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Description: QPSO和FDTD相结合的英文文章，费了好大劲找到的-FDTD combined QPSO and English articles, and with great enthusiasm to find
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Size: 2043904 |
Author: 王旭 |
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Description: 量子粒子智能群算法
QPSO
matlab程序源码-Quantum Particle Swarm Intelligence
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Size: 2048 |
Author: wang |
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Description: matlab编程的量子粒子群算法!!!!!!!!(QPSO by MATLAB!!!!!!)
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Size: 3072 |
Author: x33
|
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Description: qpso的源码和相关注释，QPSO算法的MATLAB源码，给需要的人，(Global convergence of the PSO algorithm can be used for the development of intelligent computing)
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Size: 1024 |
Author: 小贱小怂 |
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Description: 量子粒子群算法：因为粒子的位置和速度在量子空间中不能一起确定，所以用波函数表示粒子位置，通过蒙特卡罗方法求出粒子位置。gbest求解通过平均最好位置mbest得到。mbest是所有个体平均最优，通过它来求解粒子出现在相对点的位置，用L表示。而粒子的势表示位置的最终值，与L直接相关。(Quantum particle swarm optimization (QPSO): because the position and velocity of the particle can not be determined together in the quantum space, the position of the particle is expressed by the wave function, and the particle position is obtained by the Monte Carlo method. The gbest solution is obtained through the average best position of mbest. Mbest is the average optimum of all individuals, and it is used to solve the location of particles appearing at relative points, and it is expressed by L. And the particle potential indicates the final value of location, which is directly related to L.)
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Size: 1024 |
Author: 加加加 |
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