搜索资源列表
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
PSONet
- 应用PSO训练神经网络Visual C++ 训练结果优于BP,该方法用于模式识别、知识挖掘等-PSO application for training the neural network training Visual C BP superior results, the method for pattern recognition, knowledge mining, etc.
PSOt
- 智能优化算法： 粒子群优化算法（PSO）应用于神经网络优化程序。分为无隐含层、一隐含层、二隐含层。运行DemoTrainPSO.m即可。 程序来自：Brian Birge NCSU-intelligent optimization algorithms : Particle Swarm Optimization (PSO) used neural network optimization procedures. Divided into hidden layer, a hidden
vc_pso719
- 粒子群算法的示例程序，不错。可用来进行函数优化、神经网络训练等。-PSO algorithm sample program, yes. Available for function optimization, neural network training.
Class_Cover_PSO_FNN
- 基于类覆盖算法和粒子群优化的神经网络解决模式分类问题-algorithm based on the type coverage and PSO the neural network model to solve classification problems
fhycnetpsoCFM3.m
- 利用改进粒子群训练bp神经网络的matlab程序-improved PSO training bp neural network Matlab procedures
pso_train_NN
- PSO算法具有快速收敛而且有很强的跳出局部最优从而找到全局最优点的能力，故可以用它来训练优化神经网络，此程序主要研究这个方面。-PSO algorithm is fast and has a strong convergence of jumping out of the local optimal thus find the most advantages of the overall capacity, it can be used to train the neural network o
psopcnn
- 基于粒子群优化算法(PSO)确定参数的脉冲欧和神经网络滤波方法。利用粒子群优化算法(PSO)确定pcnn图像滤波参数，对图像进行滤波
psoTRAINbp
- 用PSO训练BP神经网络(matlab程序)
chapter_PSO
- 基于PSO优化的SVM算法，它可以用来预测分类(SVM algorithm based on PSO optimization can be used to predict classification.)
案例8
- 利用PSO优化GRNN案例，准确度上可能有问题(Using PSO to optimize GRNN)
PSO-BP
- 粒子群算法优化BP神经网络，在传统PSO算法的基础上增加了惯性权重，并且线性递减策略改变。(Particle Swarm Optimization (BP) algorithm optimizes BP neural network, and inertia weights are added based on traditional PSO algorithm, and linear decreasing strategy changes)
利用PSO训练BP神经网络的MATLAB源码 (1)
- PSO优化BP网络，能有效优化BP网络的权值和阈值，可在matlab上直接运行(PSO optimizes the BP network, it can effectively optimize the weight and threshold of BP network, and can run directly on MATLAB.)
PSOTrainBP
- BP神经网络容易陷于局部极小值，PSO算法在无约束非线性函数优化方面性能优越，通常可以直接找寻到全局最优解，即使不能搜多到全局最优解，也距离全局最优点不远。当然，基本PSO算法陷入局部极值也是有的。对于这个缺点目前还没有找到比较有效、省市的解决方案。本案例实现利用PSO算法和BP算法共同训练神经网络，先将网络进行PSO算法训练，然后BP算法接着进行小范围精细搜索，PSO算法训练神经网络的本质就是将输出误差函数（即能量函数）看成目标函数，PSO对能量函数进行全局寻找最小值。(BP neural n
pso-bp
- 采用粒子群算法优化BP神经网络，解决了陷入局部小的问题，同时提高了算法精度，可实现多输入单输出，或者多输入多输出，算法精度较高。
pso_bp软土路基沉降
- 用pso对bp神经网络进行优化，对软土路基进行沉降预测(Using PSO to optimize BP neural network to predict the settlement of soft soil subgrade)
matlabprogram
- 智能优化算法及其MATLAB仿真实例，包括进化类算法，群智能算法，模拟退火算法，禁忌搜索算法，神经网络算法等程序源码(Intelligent optimization algorithm and MATLAB simulation examples, including evolutionary algorithm, swarm intelligence algorithm, simulated annealing algorithm, tabu search algorithm, neural
scmt.m
- 用PSO-BPNN算法对时间序列数据进行拟合并预测未来一段时间数据(Using pso-bpnn algorithm to predict the future time series data)
pso-elm
- 极限学习机，单隐层前馈神经网络，算法源程序。(Extreme learning machine, single hidden layer feedforward neural network, algorithm source code.)
pso-bp 优化pid
- pso-bp 优化pid，粒子群算法优化bp神经网络