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粒子群优化算法C
- 同遗传算法比较,PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化,神经网络训练,模糊系统控制以及其他遗传算法的应用领域-comparison with the genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function op
粒子群算法程序以及优化神经网络程序
- 粒子群算法程序以及优化神经网络程序,测试通过
bp.pso.rar
- 标准BP神经网络算法程序:动量BP算法程序:% 调用 TRAINGDX 算法训练 BP 网络 粒子群优化神经网络源程序,The standard BP neural network algorithm procedure: momentum BP algorithm procedure: TRAINGDX called BP network training algorithm particle swarm optimization neural network source code
PSOGABPDRNN.rar
- 此包含有遗传算法、粒子群算法、BP算法优化对角递归神经网络的MATLAB程序,This includes genetic algorithms, particle swarm optimization, BP algorithm for diagonal recurrent neural network of the MATLAB program
psoBP.rar
- 基于粒子群的BP神经网络算法的MATLAB实现(源程序),基于粒子群的BP神经网络算法的MATLAB实现(源程序)
psobp
- 该文件是使用粒子群算法来求解BP神经网络饿最优解,进而对样本数据训练学习-The document is the use of particle swarm optimization to solving hunger BP neural network the optimal solution, and then the training sample data for the study
PSO_BP
- 基于粒子群和BP神经网络的混合优化策略算法。将改进PSO算法与BP神经网络结合,用PSO算法取代梯度下降法来优化神经网络的连接权值和阈值。程序简单易懂。-Based on Particle Swarm and the BP neural network algorithm for hybrid optimization strategy. Will improve the PSO algorithm and BP neural network, using PSO algorithm to re
POS-GA
- 一篇关于粒子群算-遗传算法优化BP神经网络的文章,应用背景股票预测。-Article on the particle swarm optimization- genetic algorithm BP neural network articles, application background stock forecasting.
Parrecasting
- 混沌粒子群算法的神经网络短时交通流预测Particle swarm optimization based on chaotic neural network short-term traffic flow forecasting-Particle swarm optimization based on chaotic neural network short-term traffic flow forecasting
粒子群PID
- 该代码为基于pso算法优化的PID神经网络的系统控制算法(The code is based on the PSO algorithm optimized PID neural network system control algorithm)
MATAB神经网络30个案例分析
- 该PDF共有30个MATLAB神经网络的案例,包括BP、RBF、SVM、SOM、Hopfield、LVQ、Elman、小波等神经网络;还包含PSO(粒子群)、灰色神经网络、模糊网络、概率神经网络、遗传算法优化等内容。本PDF作为本科毕业设计、研究生项日设计、博士低年级课题设计参考书籍,同时对广大科研人员也有很高的参考价值。(The PDF has a total of 30 MATLAB in the case of neural networks, including BP, RBF, SVM
粒子群算法源代码
- 改进的粒子群算法,与遗传算法,神经网络,模拟退火等算法相结合(An improved particle swarm optimization algorithm combined with genetic algorithm, neural network, simulated annealing algorithm and so on)
粒子群神经网络仿真股票分析包
- 粒子群神经网络仿真股票分析包,可以直接拿来利用,只要输入股票的相关数据,即可仿真出相应的结果。(The PSO neural network simulation of the stock analysis package can be used directly. As long as the related data of the stock are input, the corresponding results can be simulated.)
神经网络 粒子群
- 通过神经网络去拟合数据,用粒子群去优化参数(The neural network is used to fit the data and the particle swarm optimization is used to optimize the parameters)
粒子群算法优化RBF网络
- 粒子群算法优化RBF网络,有相关解释,matlab源码!可以跑通(Particle swarm optimization RBF network, there are relevant explanations, matlab source code! You can run through.)
基于神经网络的智能微电网多目标优化算法
- 智能微电网中利用粒子群算法实现微电网多目标优化(Multi-objective optimization of microgrid based on Particle Swarm Optimization in smart microgrid)
粒子群优化算法优化BP神经网络的源代码
- 粒子群优化算法优化BP神经网络的源代码,基础的值得参考下(Particle swarm optimization algorithm to optimize the source code of BP neural network)
基于粒子群和BP神经网络的混合优化策略算法
- 改进粒子群算法,比较完整,自己收集的,可以运行(Improved particle swarm optimization)
神经网络入门13课源码
- 神经网络入门13课源码 第一课 MATLAB入门基础 第二课 MATLAB进阶与提高 第三课 BP神经网络 第四课 RBF、GRNN和PNN神经网络 第五课 竞争神经网络与SOM神经网络 第六课 支持向量机( Support Vector Machine, SVM ) 第七课 极限学习机( Extreme Learning Machine, ELM ) 第八课 决策树与随机森林 第九课 遗传算法( Genetic Algorithm, GA ) 第十课 粒子群优化( Part
遗传粒子群优化算法-GAPSO
- 混沌粒子群优化算法,及其该算法的简单应用(A SIMPLE IMPLEMENTATION OF THE PARTICLE SWARM OPTIMIZATION)