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 new scaling kernel support vector regression was proposed for nonlinear system identification problem.
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。
A support vector regression method based on classification is presented to solve the nonlinear regression problem with unknown data distribution and mathematical model.
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。
Online identification algorithm of support vector regression is used to build the inverse model for the plant.
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。
The method of the conical thread image detection based on the support vector regression is presented.
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.
提出一种基于支持向量回归机的说话者确认方法。
A speaker verification system based on support vector regression machine (SVR) is presented in this paper.
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。
This paper applies a new data mining method based on SVR (support vector regression) in the prediction of the spare parts requirement.
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。
An error correction method for three axial fluxgate sensor based on support vector regression (SVR) is proposed.
支持向量回归机是求解回归问题的新的十分有效的方法。
The support vector machine (SVM) is a very effective method for regression issue.
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 method of outlier detection in regression is proposed making use of the character of structure risk function and KKT condition in support vector regression.
以锥形螺纹为研究对象，提出了一个基于支持向量回归的机械零件直线边缘亚像素图像检测方法。
Taking the conical thread as the object of study, a sub-pixel image detection method for the mechanical part linear edge based on the support vector regression was proposed.
针对可靠度计算问题中极限状态函数比较复杂或为隐式的情况，提出了一种基于支持向量回归的响应面可靠度计算方法。
On the complicated or implicit limit state functions in the reliability problems, a response surface method for reliability computation based on Support Vector Regression (SVR) is presented.
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。
Support Vector regression is an important kind of method for regression problems. The predicting speed of Support Vector regression is proportional to its sparseness.
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 support vector regression method is used for modeling the nonlinear process, and the predictive functional control method is used to control.
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。
A modeling method for nonlinear dynamic system based on Support Vector Regression (SVR) was proposed in this paper.
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(SVR)is used for the time series analysis and prediction to resolve the complex nonlinear system modeling problems.
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。
Tracking random targets with Support Vector Regression (SVR) is studied and compared with the Least Square (LS) estimate in this paper.
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。
The experiments on several pattern classification problems show that HS-LSSVM has high sparseness while holds good classification performance and its sparse process is fast.
提出一种基于支持向量回归的预测驾驶座椅主观舒适度的方法。
The SVR developed and validated using data collected from 12 subjects, and the subjects evaluated five different driving seats.
提出一种基于支持向量回归的预测驾驶座椅主观舒适度的方法。
The SVR developed and validated using data collected from 12 subjects, and the subjects evaluated five different driving seats.
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