搜索资源列表
online-svr
- online support vector regression and the companied thesis/document
SVR
- 支持向量机方面的，是Steve R Runn的svm工具箱的说明文件，-Aspects of support vector machine is the Steve R Runn documentation svm toolbox, huh, huh
SVR
- Support vector regression code
SVR
- 有关SVR SVM 的基础知识，和相关的期刊文章-The basics of the SVR SVM, and related journal articles
002-svr
- SVR tutorial Document
SVR
- Support Vector Machine介绍-Support Vector Machine
Localization-based-on-LS-SVR-in-WSN
- 文章针对无线传感器网络(WSN)节点定位算法DV-Hop的节点间距离沽计误差对定位准确度影响较大的问题，提出一种基于LS-SVR(最小二乘支持向量回归机)的定位算法L-LSSVR. -Aiming at solving the problem of the significant influence of distance estimation error onlocation accuracy of DV-Hop in Wireless Sensor Networks (WSN), a n
tutorial1.8
- LS-SVR1.8工具箱及使用说明,最小二乘支持向量机-LS-SVR MATLAB
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- 非线性控制系统的支持向量机辨识建模研究 针对非线性控制系统辨识建模难的问题， 系统研究了基于支持向量机的非线性控制系统的辨识建模理论和方法， 然后利用回归型支持向量机( Support Vector Regression， SVR) 设计了一个非线性控制系统的辨识建模系统 仿真试验结果表明， SVR 具有很高的建模精度和较强的泛化能力， 从而验证了该辨识方法的有效性和先进性。-Nonlinear Control Systems Support Vector Machine Iden
tixingguanzi2
- 分析了支持向量回归机在能源需求预测中的优势,确定了输入向量集合和输出向量集合,建立了基于Matlab技术的SVR能源需求预测模型.对我国1985-2008年能源需求相关数据进行模拟与仿真,并对中国2010年和2020年能源需求量进行预测.研究结果表明:一是中国未来对能源的需求量逐渐增加,从2010年的330400万吨标准煤上升到2020年418320万吨标准煤,年均增长率为2.39％；二是在解决我国能源系统小样本.非线性及高维模式识别问题中SVR比BP神经网络等方法有更高的预测精度.-Suppo
SVR
- 基于支持向量机的短波信号盲均衡算法，该算法稀疏性好，性能稳定。-SVM shortwave signal blind equalization algorithm based on the algorithm sparsity, and stable performance.
svm.cpp
- This a weighted svr in matlab -This is a weighted svr in matlab
toturial-on-SVR
- this file is tutorial about support vector regression and is very useful for basic persons that want learn about SVR-this file is tutorial about support vector regression and is very useful for basic persons that want learn about SVR
svr_trainer
- SVR trainer Matlab Code
matlab_SVM-chaopingmian
- 主要是描述在MATLAB中进行SVR超平面的推导过程，对于理解超平面的确定有很强的指导性-Mainly described in the MATLAB SVR hyperplane derivation process, to understand the determination of hyperplane has a strong guidance
chpp3A10.1007p2F11527503_31
- epsilon-huber支持向量回归逐步推导以及详细证明，对深入理解SVR以及后续的代码编写过程有帮助。-epsilon-huber SVR gradual derivation and detailed proof of the SVR-depth understanding of the process and the subsequent coding help.
Multistock SVR Stock Prediciotn
- Stock Variables for multidimensional SVR
PSO-optimized-SVR-master
- POS-SVR开源代码 里面有举例 可以跟着小例子试着做 且有部分注释(POS-SVR Open Source contains examples that can be tried with small examples and some comments)