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twice-update-PSO
- 本文二次更新型粒子群算法（ TUPSO）的基本思想是：一方面，在保留粒子群算法中快速收敛， 易于实现， 调整参数少等优势的前提下，通过融合基本粒子群算法中的信息共享原理与 DPSO-TSP 中的 2-Opt 运算法则，改进了DPSO-TSP中粒子进化的规则-In this paper, the basic idea of the new particle swarm optimization (TUPSO) algorithm is: on the one hand, by integratin
pso
- 粒子群优化算法 改进粒子群优化算法的典型例子 易懂易学-Particle swarm optimization algorithm A typical example of improved particle swarm optimization algorithm is easy to understand
PSO-LSSVM
- 利用改进PSO算法对LS-SVM进行参数优化，参数 和 的取值范围分别为 和 ，粒子种群数量为 25，迭代次数为 100，惯性权重因子 和 取0.9和0.1，学习因子 和 均取2。-The parameters of PS-SVM are optimized by using the improved PSO algorithm. The range of parameters is 25, the number of particles is 25, the number of iterati
粒子群算法程序
- 粒子群算法的程序，主要是针对基本粒子群和改进粒子群算法。(Particle swarm optimization procedures, mainly for the basic particle swarm optimization and improved particle swarm algorithm.)
LinWPSO
- 权重改进的粒子群算法（线性递减权重法），让惯性权重从最大值线性减小到最小值(Weights to improve particle swarm optimization (linear decreasing weight method), so that inertia weight decreases linearly from maximum to minimum)
All_Clu
- K-means，PSOKM，ACKM三种聚类算法，数据集适用于K-means，在PSO上效果不好，AC有改进(Including K-means, PSOKM, ACKM three clustering algorithms, the data set applies to K-means, clustering on PSOKM is not good, clustering in ACKM has improved.)
PSO+DOA
- 改进粒子群算法在DOA估计中的应用Application of improved particle swarm optimization in DOA estimation(Application of improved particle swarm optimization in DOA estimation)
粒子群优化算法以及改进的PSO算法代码matlab
- 粒子群算法及其改进，在原有粒子群算法基础上进行改进，增加免疫算法，使其尽快跳出早熟，收敛更快，结果更优！(Particle swarm optimization (PSO) and its improvement are improved on the basis of the existing particle swarm algorithm, and the immune algorithm is added to make it jump out of premature, faster
Epso
- 改进版的pso， 收敛速度更加快，而且不会陷入局部最优(The improved version of PSO has faster convergence and does not fall into local optima.)
www.dssz.com_pso-bp
- 基于神经网络的局限性，使用粒子群算法优化其权值，对其进行改进(PSO improved neural network)
改进粒子群算法工具箱
- 改进的pso算法 ，本人已经验证通过，解压后就可以使用
改进pso可以求解城市数量大的旅行商问题
- 城市数量最大的改进的粒子群算法求解旅行商问题(Particle swarm optimization for traveling salesman problem)
ypap115-path-planning
- 粒子群算法路径规划，可以直接运行，可以在此基础上继续改进嗯嗯嗯嗯(Particle swarm algorithm for path planning, can be directly run, can be the basis to continue to improve, huh)
pso2
- 粒子群比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。(It is more simple than the genetic algorithm rule. It doesn't have the crossover (Crossover) and the Mutati
m文件
- 改进遗传算法优化实例，用于系统辨识优化控制。(An example of improved genetic algorithm is applied to system identification and optimal control.)
pso1
- 基于粒子群算法的移动机器人路径规划，文件是关于粒子群算法求解路径规划的问题，其中包括栅格障碍物环境的建立，粒子群及其改进算法的仿真程序。(On path planning problem of particle swarm algorithm matlab code)
PSO-SVM
- 将改进的粒子群算法和GA与SVM相结合，通过参数寻优构建新模型完成对空气质量指数的预测(The improved particle swarm optimization and genetic algorithm are combined with SVM. The prediction of air quality index (AQI) is completed by constructing a new model by parameter optimization.)
PsoProcess_Micro_Grid
- 在假设负荷预测、风机和光伏未来出力已完全准确的情况下（允许弃风弃光），采用改进PSO算法对某含有风机、光伏、以及常规负荷的微电网未来24 小时的出力调控进行日前优化，以实现经济性最优(Under the assumption that the load forecasting, the wind turbine and the future power of the photovoltaic power are completely accurate (allowing for abandonm
A-NSGA-III
- 新版改进NSGA算法A-NSGA-III，用于软件仿真平台对比于MOEA/D,PSO等多种算法。(The new version of improved NSGA algorithm a-nsga-iii is used for software simulation platform comparison with MOEA/D,PSO and other algorithms.)
PSO_adaptation
- 改进型粒子群PSO优化算法MATLAB代码，基于权重改进速度，已封装为函数(Improved particle swarm optimization algorithm PSO MATLAB code, based on the speed of weight improvement, has been encapsulated as a function.)