搜索资源列表
fxxkzxtdzcxljbsjmyj
- 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
regress-and-predict
- 基于svm的一维信号的回归预测，精确度优于传统的神经网络方法-The one-dimensional signal based svm regression prediction accuracy is better than traditional neural network method
!
- dna分类 2000数学建模a题 线性回归 最小二乘法 函数定义-dna Category 2000 issue of mathematical modeling a least squares linear regression function definition
a-MATLAB-library-for-robust
- 介绍一个稳健性分析工具箱。主要做稳健性主成分、主成分回归、分类。-Our toolbox currently contains implementations of robust methods for location and scale estimation, covariance estimation (FAST-MCD), regression (FAST-LTS, MCD-regression), principal component analysis (RAPCA, ROB
LASSOaLARSa-SPCA
- Abstract There a number of interesting variable selection methods available beside the regular forward selection and stepwise selection methods. Such approaches include LASSO (Least Absolute Shrinkage and Selection Operator), least angle regression (
Partial-least-squares-
- 数学建模中基于matlab的偏最小二乘回归分析算法-Mathematical modeling matlab-based partial least squares regression analysis algorithm
data-mining
- SPSS下数据挖掘实例，关于BMI和心血管疾病的逻辑回归分文分析，包括原始数据分析过程和论文-The following examples of SPSS data mining on BMI and cardiovascular disease penny logistic regression analysis, including raw data analysis process and papers
lec5
- Li near r egr essi on, acti ve learning We arriv ed at the lo gistic regression model when trying to explicitly model the uncertainty about the lab els in a linear c la ss ifier. The same genera l modeling approach p e rmits us to use line a
BPalgrithm
- 描述了BP神经网络在回归分析中的应用研究，有比较详细的分析数据-Describes the application of BP neural network in the regression analysis, a more detailed analysis of data
the-maximum-likelihood-estimate
- 1、 极大似然估计 尝试用0~24阶多项式拟合，并用5折交叉验证选择最佳模型（多项式阶数及其系数，给出类似课件中的图），并画出最佳模型的拟合效果图（类似图1，蓝色点为训练样本、红色点为测试样本、绿色线为模型预测），给出该模型的测试误差。 2、 岭回归 多项式阶数为24，正则系数λ的取值范围为exp(-19)到exp(20)，采用并用5折交叉验证选择最佳模型。实验结果要求同1。 -1, the maximum likelihood estimate of 0 to 24 try-o
xianxinglvbomatlab
- 详细介绍了自回归技术公式,同时采用此技术模拟具有空间相关性的随机风荷载,给出了用自回归技术模拟脉动风荷载的步骤以及具体MATLAB程序,并把所编程序用于江阴长江大桥风荷载模拟,结果表明效果较好。 - Details of the formulas from regression techniques, while using this technology to simulate the spatial correlation of random wind loads, gives ste
XIANXINGLVBO
- 详细介绍了自回归技术公式,同时采用此技术模拟具有空间相关性的随机风荷载,给出了用自回归技术模拟脉动风荷载的步骤以及具体MATLAB程序,并把所编程序用于江阴长江大桥风荷载模拟,结果表明效果较好。 更多还原-Details of the formulas from regression techniques, while using this technology to simulate the spatial correlation of random wind loads, gives ste
muhushenjing
- 模糊神经网络可用于模糊回归、模糊控制器.-Fuzzy neural network can be used for fuzzy regression, fuzzy controller
l
- STATA CODE for estimate autocorrelation after regression. good work and excelent. stata easy to use.
h
- STATA CODE for estimate autocorrelation after regression. good work and excelent. stata easy to use.
LMADURHXT
- STATA CODE for estimate autocorrelation after regression. good work and excelent. stata easy to use.
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
Image-Denoising-by-Adaptive-Kernel-Regression
- This paper introduces an extremely robust adaptive denoising filter in the spatial domain. The filter is based on non-parametric statistical estimation methods, and in particular generalizes an adaptive method proposed earlier by Fukunaga [1]
CharlesLiSVR1.2
- 支持向量回归机工具箱。自编。带有GUI界面和使用教程。基于PCA降维和遗传算法寻优-Support vector regression toolbox. Self. With a GUI interface and tutorials. PCA dimensionality reduction based and genetic algorithm optimization
Support-Vector-Machine.txt
- 使用支持向量机进行非线性回归，得到非线性函数y=f(x1,x2,…,xn)的支持向量解析式， 求解二次规划时调用了优化工具箱的quadprog函数。-Support Vector Machine for Nonlinear Regression