搜索资源列表
psobp
- 用pso算法优化BP网络，简单易懂 可以在此基础上进行其他改进-Optimized BP network with pso algorithm is simple and easy to understand can make additional improvements on this basis
daimayasuo
- 包含：基于蚁群算法求解对称非对称旅行商问题 粒子群优化算法演示(PSO) 基于遗传算法(GA)的多变量旅行商问题(TSP) 遗传算法优化BP 神经网络在数据预测方面的应用 金融数量分析相关代码-Comprising: Solving Symmetric Asymmetric Traveling Salesman Problem Based on Ant Colony Algorithm Particle Swarm Optimization Demo (PSO) Mult
nanbao_v16
- 计算目标和海洋回波的功率谱密度,BP神经网络的整个训练过程,基于K均值的PSO聚类算法。- Calculating a target and ocean echo power spectral density, The entire training process BP neural network, K-means clustering algorithm based on the PSO.
feipen
- 空间目标识别，采用PM算法，BP神经网络的整个训练过程,基于分段非线性权重值的Pso算法。- Space target recognition algorithm using PM, The entire training process BP neural network, Based on piecewise nonlinear weight value Pso algorithm.
M_rw_Excel
- 在Matlab中PSO算法可用于BP神经网络的网络权值优化,PSO算法比传统的BP神经网络采用误差反向传播来调整网络连接权值可以有更大的空间内搜索的优势。-The PSO calculate way can be used for the network power of BP nerve network to be worth in Matlab excellent turn, the PSO calculate way is more anti- than traditional BP ne
Matlab-GP-nn-algorithmic-optimize
- 在Matlab中PSO算法可用于BP神经网络的网络权值优化,PSO算法比传统的BP神经网络采用误差反向传播来调整网络连接权值可以有更大的空间内搜索的优势。-The PSO calculate way can be used for the network power of BP nerve network to be worth in Matlab excellent turn, the PSO calculate way is more anti- than traditional BP ne
psobp
- pso优化后的bp神经网络，何以很好的克服bp神经网络的缺点-The disadvantage pso optimized bp neural network, how good overcome bp neural network
haihou_v60
- FMCW调频连续波雷达的测距测角，BP神经网络的整个训练过程,基于K均值的PSO聚类算法。- FMCW frequency modulated continuous wave radar range and angular measurements, The entire training process BP neural network, K-means clustering algorithm based on the PSO.
To-predict
- matlab预测程序集合，适用于数学建模大赛，直接数据导入就可以用。包括灰色模型预测程序2个，gm10，greymodel，高斯混合模型mixture_of_gaussians，以及BP神经网络优化模型，遗传算法优化，Genetic，粒子群算法优化，PSO-Matlab to predict collection, suitable for mathematical modeling contest, data import can use directly. Including gray mo
PSOBP
- PSO优化后的BP神经网络，用于风速预测得训练和输出-BP network with PSO
sai-tb67
- BP神经网络的整个训练过程,基于混沌的模拟退火算法，基于分段非线性权重值的Pso算法。- The entire training process BP neural network, Chaos-based simulated annealing algorithm, Based on piecewise nonlinear weight value Pso algorithm.
pso_bp
- pso算法从随机解出发，通过迭代寻找最优解，通过适应度来评价解的品质，粒子群优化Bp网络源程序，仅供参考-pso algorithm random solutions, through iterative find the optimal solution, quality, particle swarm to uate the fitness solution by optimizing Bp network source code, for reference only
PSO_BP
- 粒子群优化BP神经网络算法，采用PSO优化神经网络的结构层个数，及隐含层的权值，相较BP神经网络，预测效果更好-Particle swarm optimization BP neural network algorithm, using PSO to optimize the number of neural network structure layer, and the value of the hidden layer, compared to BP neural network, the
yanqoupan
- BP神经网络用于函数拟合与模式识别，基于K均值的PSO聚类算法,使用拉亚普诺夫指数的公式。- BP neural network function fitting and pattern recognition, K-means clustering algorithm based on the PSO, Raya Punuo Fu index using the formula.
Image-filter.tar
- 提出了一种基于改进 BP 神经网络和粒子群优化算法( PSO) 的图像滤波方法 。该方法利用双曲正切形式 的误差函数代替 BP 神经网络传统的最小均方误差函数( LMS),并将改进后的 BP 神经网络利用 PSO 算法优 化,用来减小图像噪声对神经网络精度的影响以及避免神经网络陷入局部极小值点,从而提高神经网络去噪能 力。实验结果表明,与传统滤波方法相比,该方法不仅能有效地滤除图像中的高斯噪声而且能很好地保护图像 细节 。- U63D0 u51FA u4E86 u4E00
matlab
- Matlab中关于PSO优化BP神经网络的实例，以及具体的代码(An example of PSO optimization of the BP neural network in Matlab and the specific code)
PSO_BP
- 一个利用PSO粒子群优化算法训练BP神经网络的程序，在matlab环境中进行操作，代码简便可行。(PSO optimization neural network)
神经网络
- 用matlab编程进行神经网络算法的运用。内部含有SVM及SVM的改进，PSO算法，BP算法等等。(Matlab programming for the use of neural network algorithm. Internal SVM and SVM improvement, PSO algorithm, BP algorithm and so on.)
MATLAB智能算法30个案例分析代码
- 压缩包内是关于BeiHang出版的matlab智能算法30个案例的代码，对于学习理解智能算法的原理和编程有一定的帮助。如遗传算法、粒子群算法、免疫优化算法、模拟退火算法、BP算法等。(there are 30 matlab codes, which match a book about intelligence algorithms,such as genetic algorithms, PSO, ACO,BPO,etc. WISH that will be help for you.)
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