搜索资源列表
SVM
- SVM神经网络的信息粒化时序回归预测 遗传算法的典型实例-SVM neural network information granulation typical examples of the time series regression to predict genetic algorithm
SVC-SVR
- 该压缩包中包含的程序均在MATLAB下开发，从功能上分为两类。第一类名字中包含SVC的程序，主要用来对两类数据进行分类，并可以生成分类结果图。第二类名字中包含SVR的程序，主要用来对高维数据集进行预测，并可以生成预测结果图。该类程序可以很好地解决SVM中的分类及预测问题。-The archive contains the MATLAB program are under development, from the functions are divided into two categories
SVM
- SVM的SMO算法实现，svm_train为训练函数，svm_predict为预测函数，按说明输入参数即可-The SMO SVM algorithm, svm_train of the training function, svm_predict to predict function, follow the instructions to input parameters
The-code-for-SVM-model
- 采用支持向量机算法进行股市回归预测分析的程序，本人亲自尝试，可以正常使用。对于使用SVM算法的同学很有帮助！-Using support vector machine algorithm to predict the stock market regression analysis procedures, I personally try to be normal. For SVM algorithm helps the students!
waveletsvm_longchuan
- 可以用于预测的小波分解下的支持向量回归机-wavelet svm for predict
SVM-predict
- 一个matlab例程，基于SVM的信息粒化时序回归预测demo，实现了对上证开盘指数变化趋势和变化空间预测- A matlab routine, regression forecasting demo SVM-based information granulated timing to achieve the opening of the Shanghai index trends and changes in spatial prediction
SH
- 利用SVR对上证的指数进行预测，输入数据具有良好的效果，得到的结果还是比较理想的-The use of SVM to the Shanghai index to predict the input data with good results, the result is quite satisfactory
SVM_lusifa
- 用于求解支持向量机的二分类问题，对于现实问题进行预测分类-For solving SVM binary classification problem, for reality to predict classification
My_example1_predict
- SVM做分类回归程序已经调试完成 使用的是libsvm matlab -SVM method for regression and predict
SVM
- 使用支持向量机算法对二分类问题进行预测，实现大数据分析的目标。(Support vector machine algorithm is used to predict the two classification problem, and achieve the goal of large data analysis.)
psosvm
- 粒子群优化支持向量机对电池寿命进行预测，利用粒子群优化支持向量机参数(Particle swarm optimization support vector machine is used to predict battery life, and particle swarm optimization is used to support SVM parameters)
prediction SVM
- 用SVM做预测的matlab程序,内部程序详细，包含数据(a program to predict time series)
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.)
pso-svm电力负荷预测
- 电力负荷预测是电力系统规划的重要组成部分，也是电力系统经济运行的基础，其对电力系统规划和运行都极其重要。利用粒子群算法优化支持向量机更加高效准确预测电力负荷。(The power load forecasting is an important part of the power system planning, and it is also the basis of the economic operation of the power system. It is very important