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------名称：带交叉因子的改进PSO算法
------功能：求解多维无约束优化问题
------特点：收敛性强，还可以加入变异算子,------ Name: with cross-factor function to improve the PSO algorithm ------: Solving multi-dimensional unconstrained optimization problem ------ characteristics: strong converge
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粒子群算法，根据自己需要可以更改里面的参数具体情况自己更改-Particle swarm optimization, in accordance with their needs can change the parameters inside the specific circumstances of their own change
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在传统的子载波分配过程中，具有优先权的用户将优先选择最好的载波，这将导致载波利用效率下降。
许多改进算法通过牺牲一定的公平性来提升容量并降低复杂度，但是这可能会使用户间无法达到所要求的公平
性。针对这些问题，提出了一种基于公平度门限的载波和功率自适应分配算法。在载波分配过程中，通过公平度
门限来决定载波分配优先级，从而实现容量和公平度的粗略折中。载波分配后利用粒子群（PSO）算法进行功率分配来达到所要求的公平度门限。实验结果表明，该算法在满足所要求公平度门限的同时提升了系统容量。 -
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该文件为粒子群算法优化支持向量机模型参数的matlab代码 支持向量机模型为专门用于处理不平衡数据的成本控制型支持向量机模型-Matlab code of the file support vector machine model parameters for particle swarm optimization support vector machine model for cost control, support vector machine model for dealing wit
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Particle Swarm Optimization with different ineria weights
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标准PSO算法代码采用C++编制；注释丰富；带有测试函数；测试函数在（0，-1）处取得最小值3。编译运行通过修改优化模型即可直接用来优化你所需求解问题,本人在弹道优化方面已测试成功。代码内总共进行50次pso搜索运算，以提高算法的可靠性，迭代最大次数限制在500次以内，输出最佳适应值和取得最佳适应值时的迭代次数，平均进行每次pso运算要多少次迭代才能得到满足条件的解-Standard PSO algorithm using C++ code compiled Notes rich with
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粒子群算法源程序与带交叉因子的粒子群优化算法-Particle swarm algorithm source and particle swarm optimization algorithm with cross Factor
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标准粒子群算法在MATLAB中的实现。其主要思想是根据带惯性权重w的PSO算法实现。-Realization of Standard Particle Swarm Optimization in MATLAB. The main idea is to realize the PSO algorithm with inertia weight w.
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粒子群算法PSO和万有引力算法GSA结合优化FNN神经网络进行标准数据集的分类-Particle swarm optimization algorithm PSO and universal gravitation algorithm GSA combined with FNN neural network to optimize the classification of standard data sets
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this source code for pso. particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. It solves a problem by having a population
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PSO Powerflow with UPFC
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使用粒子群算法以经济性为目标对微网系统进行优化(Using particle swarm optimization (PSO) to optimize the micronetwork system with the goal of economy)
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Abstract: With the development of engineering technology and the improvement of mathematical model, a large number of optimization
problems were developed from low dimensional optimization to large-scale complex optimization. Large scale global opti
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Abstract: With the development of engineering technology and the improvement of mathematical model, a large number of optimization
problems were developed from low dimensional optimization to large-scale complex optimization. Large scale global opti
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粒子群算法与多目标优化问题的结合，解决背包问题实例(Combining particle swarm optimization with multi-objective optimization, we solve knapsack proble)
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用粒子群算法对BP神经网络进行训练
亲测可用！(BP Neural Network Training with Particle Swarm Optimization Pro-test is available!)
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采用粒子群算法求解多目标优化问题，有注释(Using particle swarm optimization to solve multi-objective optimization problems with annotations)
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未来高比例可再生能源电力系统愿景下，具有波动
性和不确定性的风/光等可再生能源作为主要能源供应者，给
电力系统带来了巨大的灵活性需求，考虑单一类型灵活性资
源提供调节能力的规划模型和以净负荷包络线为基础的电源
规划方法将不再适用。引入灵活性指标量化评估源荷储多类
型灵活性资源的调节潜力并作为优化决策变量纳入到规划模
型中(Under the vision of the high penetration renewable energy power systems in the futu
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文件包括带压缩因子的粒子群算法，权重改进的粒子群算法，自适应权重法，随机权重法，变学习因子的粒子群算法，异步变化的学习因子，二阶粒子群算法，二阶振荡粒子群算法，混沌粒子群算法，混合粒子群算法，杂交粒子群算法，模拟退火算法(Documents including particle swarm algorithm with compression factor, weighting the improved particle swarm algorithm, adaptive weight meth
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