支持向量回归机；
The method of the conical thread image detection based on the support vector regression is presented.
以支持向量回归为主要算法，讨论了圆锥螺纹各参数的图像检测方法。
When applied to regression and prediction, we often call SVM as support vector regression machine SVR.
当sVM用于回归分析和预测时，通常称其为支持向量回归机svr。
A new scaling kernel support vector regression was proposed for nonlinear system identification problem.
提出一种新的尺度核支持向量回归方法，并应用于非线性系统辨识问题。
A speaker verification system based on support vector regression machine (SVR) is presented in this paper.
提出一种基于支持向量回归机的说话者确认方法。
A SAR image is regarded as a 2-d continuous function and is approximated by support vector regression (SVR).
将SAR图像看作连续二维函数，利用SVR方法对其进行逼近。
Online identification algorithm of support vector regression is used to build the inverse model for the plant.
采用支持向量回归在线辨识算法作为建模方法建立被控对象的逆模型。
An error correction method for three axial fluxgate sensor based on support vector regression (SVR) is proposed.
提出了一种基于支持向量回归机(SVR)的三轴磁通门传感器误差修正方法。
Using linear programming technique and scaling kernel function, the support vector regression model was obtained.
通过线性规划技术和采用尺度函数作为核函数来实现支持向量回归模型。
Whereas SVM is not suitable for the smoothing regression, a modified support vector regression model is proposed.
鉴于后者有着对于光顺性的特殊要求，已有的支持向量机并不适用。
A modeling method for nonlinear dynamic system based on Support Vector Regression (SVR) was proposed in this paper.
提出一种基于支持向量回归机(SVR)的非线性动态系统建模方法。
Results show that support vector regression is superior in learning, and make the converted voice more inclined to the target.
结果表明，支持向量回归具有更强的学习能力，使转换语音具有更好的目标倾向性。
This paper applies a new data mining method based on SVR (support vector regression) in the prediction of the spare parts requirement.
本文将基于支持向量回归的数据挖掘方法，用于服务备件需求预测研究中。
Tracking random targets with Support Vector Regression (SVR) is studied and compared with the Least Square (LS) estimate in this paper.
本文研究了支持向量回归(SVR)在机动目标跟踪中的应用，并与传统回归方法最小二乘法(LS)进行了比较。
Parameter tuning of Support Vector Regression (SVR) has been a critical task to develop a SVR model with good generalization performance.
在回归支持向量机的建模中，参数调节问题一直是影响模型性能的重要因素之一。
A new algorithm for modeling regression curve is put forward in the paper, it combines B-spline network with improved support vector regression.
将改进的支持向量回归机与B -样条网络相结合，提出了一种建立回归曲线模型的新算法。
The Support Vector Regression(SVR)is used for the time series analysis and prediction to resolve the complex nonlinear system modeling problems.
用支持向量回归（SVR）的方法分析和预测时间序列，可解决复杂非线性系统的建模问题。
The support vector regression method is used for modeling the nonlinear process, and the predictive functional control method is used to control.
利用支持向量回归的方法对非线性过程进行建模，采用预测函数控制方法进行控制。
The generalization of the support vector regression model, the optimization of the generalization capacity, and the training speed are discussed.
同时对广泛的支持向量回归模型、优化支持向量模型的泛化能力和运算速度等方面进行讨论。
The research on support vector regression has an important theoretical and applicable significance on function regression(re-gression approximation).
支持向量回归问题的研究，对函数拟合（回归逼近）具有重要的理论和应用意义。
A method of outlier detection in regression is proposed making use of the character of structure risk function and KKT condition in support vector regression.
利用支持向量回归算法中结构风险函数较好的平滑性以及KKT条件，提出一种回归中的异常值检测方法。
A novel adaptive support vector regression neural network (SVR-NN) is proposed, which combines respectively merits of support vector machines and a neural network.
一种新的自适应支持向量回归神经网络(SVR - NN)提出，它结合了分别支持向量机和神经网络的优点。
Support Vector regression is an important kind of method for regression problems. The predicting speed of Support Vector regression is proportional to its sparseness.
支持向量回归机是一种解决回归问题的重要方法，其预测速度与支持向量的稀疏性成正比。
A support vector regression method based on classification is presented to solve the nonlinear regression problem with unknown data distribution and mathematical model.
提出了一种基于分类技术的支持向量回归方法，解决数据分布未知、数学模型未知的非线性回归问题。
Proposed the model of fuzzy chance constrained programming with fuzzy decision, and did some research on fuzzy linear support vector regression (algorithm) on this base.
给出带有模糊决策的模糊机会约束规划模型，在此基础上，研究模糊线性支持向量分类机(算法)和模糊线性支持向量回归机(算法)。
A method of outlier detection in re-gression is proposed making use of the character of structure risk function and KT condition in support vector regression in this paper.
该文利用支持向量回归算法中结构风险函数的性质以及KT条件，提出一种回归中的异常值检测方法。
A method of outlier detection in re-gression is proposed making use of the character of structure risk function and KT condition in support vector regression in this paper.
该文利用支持向量回归算法中结构风险函数的性质以及KT条件，提出一种回归中的异常值检测方法。
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