搜索资源列表
bvidmvds
- 应用小区域方差对比,程序简单,包括最小二乘法、SVM、神经网络、1_k近邻法,包含了阵列信号处理的常见算法,可以广泛的应用于数据预测及数据分析,基于分段非线性权重值的Pso算法,通过反复训练模板能有较高的识别率。- Application of small area variance comparison, simple procedures, Including the least squares method, the SVM, neural networks, 1 _k neighbor
vvtxtnnx
- 包含位置式PID算法、积分分离式PID,基于分段非线性权重值的Pso算法,添加噪声处理,使用拉亚普诺夫指数的公式,包括最小二乘法、SVM、神经网络、1_k近邻法。- It contains positional PID algorithm, integral separate PID, Based on piecewise nonlinear weight value Pso algorithm, Add noise processing, Raya Punuo Fu index using t
newthreepsotosvm
- 用粒子群算法解决SVM问题的代码,希望对大家有帮助!-Using particle swarm optimization (pso) algorithm to solve the problem of SVM code, I hope it can help you!
haijui
- 包括最小二乘法、SVM、神经网络、1_k近邻法,实现用SDRAM运行nios,同时用SRAM保存摄像头数据,基于分段非线性权重值的Pso算法。- Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Implemented with SDRAM run nios, while saving camera data SRAM, Based on piecewise nonlinear
PSO_SVM
- 带有PCA之后的数据集,并用粒子群(PSO)优化支持向量机(SVM)的分类器进行分类,并给出分类识别率。-After the data set with PCA, and use the particle swarm optimization (PSO) to optimize the support vector machine (SVM) classifier for classification, and classification recognition rate is given.
149373c
- pso-svm利用回归预测分析最佳的参数进行SVM网络训练 分析结果- pso-svm Analysis of the best use of parametric regression prediction network training SVM analysis results
SVM_GUI_3.1[mcode]
- faruto编写的基于libsvm3.1的SVM_GUI,可用于SVM分类及相关回归分析,已经集成了GA及PSO参数寻优算法及PCA算法,提供的是GUI版本及与之对应的源码版本-SVM_GUI and the program of SVM_Code,base on the version of the Libsvm 3.1,using the GA and PSO algorithm to improve
SVM_Code_GUI
- faruto编写的基于libsvm3.1的SVM_GUI,可用于SVM分类及相关回归分析,已经集成了GA及PSO参数寻优算法及PCA算法,提供的是GUI版本及与之对应的源码版本-SVM_GUI and the program of SVM_Code,base on the version of the Libsvm 3.1,using the GA and PSO algorithm to improve
pso-svm-prediction
- 该程序是基于粒子群算法优化支持向量机中的正则化参数C和核函数参数K的算法,实现了对电力负荷的短期预测,预测效果较好,可根据自己要求进行更改。-The algorithm is based on particle swarm optimization algorithm to optimize regularization parameter C and kernel function parameter K in support vector machine. It realizes the s
chapter_PSO
- 用psoSVMcgForClass.m实现对分类问题用PSO来优化SVM参数的问题-Use psoSVMcgForClass. M for classification problems using PSO to optimize parameters of SVM
chapter15_PSO
- svm 的参数优化,利用pso(粒子群优化算法)选择最优参数c g,最终提高训练集的分类准确率,更好的提高分类器性能-Svm parameter optimization, the use of pso (particle swarm optimization algorithm) to the optimal parameter c g, and ultimately improve the training set classification accuracy, better impr
4
- pso svm classification
psoSVM
- 粒子群优化支持向量机代码,可用于预测分析(Particle swarm optimization support vector machine code, can be used for predictive analysis)
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
JMcec2007
- gene selection in cancer classification by pso/svm
PSO-SVM-master
- 该代码为粒子群算法优化支持向量机模型(The code is a particle swarm optimization algorithm to optimize the support vector machine model)
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.)
psoSVMcgForClass
- 用粒子群寻优SVM,从而实现对分类器的参数实现寻优(pso svmcg for class,abcpso)
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.)
10526349 (2)
- 使用粒子群算法优化支持向量回归,实现预测功能(Support Vector Regression Using Particle Swarm Optimization)