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粒子群的优化算法，不仅可以方便地解决无约束优化问题，也可以方便的解决有约束的非线性优化问题。-Particle Swarm Optimization algorithm, not only can easily solve the unconstrained optimization problem can also be convenient to solve constrained nonlinear optimization problem.
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A novel particle swarm optimization approach for product design and manufacturing
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有关多目标粒子群算法的论文，想研究多目标的可以参考-Of the multi-objective particle swarm optimization of the papers, I would like to research objectives can refer to
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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 descr iption of the procedures
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使用基本粒子群算法整定的PID控制，供学习者参考。-The use of elementary particle swarm optimization algorithm-tuning PID control for the learner information.
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最新SD期刊上关于改进型PSO算法，我是通过学校内部数据库在SD下载的哦！包括《A dynamic inertia weight particle swarm optimization algorithm》、《Adaptive Particle Swarm Optimization》、《Cyber Swarm Algorithms – Improving particle swarm optimization using adaptive memory strategies》。这三篇都是比较有研
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粒子群算法在离散问题中的应用。这里主要是在TSP问题中的应用。-Discrete Particle Swarm Optimization Problems. Here the main problem in the application of TSP.
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一种混沌粒子群嵌入优化算法及其仿真Embedded in a chaotic particle swarm optimization algorithm and simulation-Embedded in a chaotic particle swarm optimization algorithm and simulation
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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, multi-dimensional functions can be optimized for fast, easy to fall into local optimal value
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粒子群算法的寻优算法-非线性函数极值寻优-Particle swarm optimization algorithm- Extreme nonlinear function optimization
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本程序使用支持向量机法和粒子群算法，实现对数据的分类-This program uses support vector machine method and particle swarm optimization, to achieve the classification of data
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粒子群算法的寻优算法，PSO算法是从生物种群行为特征中得到启发并用于求解最有问题，本程序以一案例说明PSO的运用。-Particle swarm optimization algorithm, PSO algorithm is population from biological and behavioral characteristics of the inspiration for solving most problems, this case illustrates the proced
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粒子群优化算法（PSO）应用于神经网络优化程序-Particle swarm optimization (PSO) algorithm is applied to the neural network optimization program
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粒子群算法的简单实现，适合初学粒子群的同学。-Particle Swarm Optimization
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本程序采用基本粒子群算法，共有8个测试函数，测试算法对复杂函数的收敛速度和收敛方差-This program uses a Particle Swarm Optimization, a total of eight test functions, test algorithm convergence speed and variance of complex functions
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人工智能的作业，是关于粒子群算法的，已经实现完成。可以参考-Artificial intelligence jobs, it s about particle swarm optimization algorithm, has been completed. You can reference
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粒子群算法(优化算法)论文设计(包括源代码实验数据_截图_很全面的)，对于粒子群算法的初学者来说是很好的参考资料-Particle swarm optimization (optimization) paper design (including source code _ screenshot _ experimental data very comprehensive), particle swarm optimization for beginners is a good referenc
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粒子群算法源程序，一个完整的粒子群算法程序，供大家一起学习和参考。-Source program of particle swarm optimization (pso), a complete procedure of particle swarm optimization (pso), for everybody to learn together and reference.
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利用粒子群优化算法寻找下列多元函数的最大值：f(x, y) = x*cos(2*pi*y) + y*sin
(2*pi*x) -2≤x≤2，-2≤y≤2
要求输出最优解、最优解对应的x和y值，以及粒子群优化算法迭代过程中的适应度函数进
化曲线。-Maximum use of particle swarm optimization algorithm to find the following
multivariate function: f (x, y) = x*
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微粒群算法的寻优算法：PSO算法参数设置、种群初始化、寻找初始极值、迭代寻优-Particle swarm optimization algorithm: PSO algorithm, parameter settings, population initialization, looking for the initial extremum, iterative optimization
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