Support vector machines (SVM) are a kind of novel machine learning methods, based on statistical learning theory, which have been developed for solving classification and regression problems.
支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。
Support vector machines (SVM) is a new nonlinear modeling method which is suitable for solving small samples and high dimension modeling problems.
支持向量机(SVM)作为一种新型的非线性建模方法，适合于处理小样本和高维数的建模问题。
Support vector machines (SVM) are a kind of novel machine learning methods based on statistical learning theory, which has been developed to solve classification and regression problems.
支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。
A face detection method based on a hierarchical support vector machines (SVM) presents improved methods for both of these problems.
提出了一种基于层次型支持向量机的正面直立人脸检测方法，在这两方面作了改进。
An E-government website assessment model based on least squares support vector machines (LS - SVM) is established using the website assessment index system which is established for E-government.
在确立了电子政务网站评估指标体系的基础上，建立了基于最小二乘支持向量机(LS-SVM)的电子政务网站评估模型。
To improve the performance of support vector machines (SVM), a hybrid kernel is constructed from the existing common kernels, and the hyper-parameters are optimized by using a quasi-Newton method.
为了提高支持向量机(SVM)的识别性能，提出了在常用内核的基础上构造一个组合内核函数，然后用拟牛顿算法对其超参数进行优化的方法。
A new method of modulation identification for communication signals, using wavelet transform to extract characteristics and based on support vector machines (SVM), is proposed.
提出了一种应用小波变换提取分类特征的基于支撑矢量机的通信信号调制识别方法。
The support vector machines(SVM) model with multi-input and single output was proposed.
建立了多输入、单输出的支持向量机（SVM）预测模型。
A new geometric fast incremental learning algorithm for support vector machines (SVM) was proposed.
提出了一种新的基于壳向量的增量式支持向量机快速学习算法。
In accordance with the features of non-linear and time varying for ferment process, a support vector machines (SVM) model is established for estimating the concentration of product.
针对非线性时变的发酵过程，建立了用于产物浓度预估的支持向量机(SVM)模型。
To the problem that the standard SVM does not provide probabilities output, the probabilistic outputs for support vector machines is modeled based on the maximum entropy estimation.
针对传统的支持向量机方法不能提供后验概率的输出问题，从信息熵的角度采用最大熵估计方法，直接对支持向量机输出进行后验概率建模。
As new technology of data mining, support vector machines (SVM) have been successfully applied in pattern recognition and regression problem, et al.
支持向量机作为数据挖掘的一项新技术，应用于模式识别和处理回归问题等诸多领域。
A phase space reconstructed forecasting method of stock price was proposed based on least squares support vector machines (LS-SVM).
提出一种基于相空间重构的最小二乘支持向量机(LS - SVM)的股票价格预测方法。
Support vector machines (SVM) based on the statistical learning theory is a new machine learning tool.
基于统计学习理论的支持向量机是一种新型机器学习工具。
On the basis of studying on least-squares support vector machines (LS-SVM) of the image edge detection technology, Proposed a new method, which is based on mixed Kernel LS-SVM image edge detection.
本文在研究了众多边缘检测方法的基础上，重点研究了最小二乘支持向量机（LS-SVM）的图像边缘检测技术，提出了一种基于混合核函数最小二乘支持向量机的图像边缘检测方法。
A nonlinear predictive control algorithm based on least squares support vector machines (LS-SVM) model was proposed.
提出一种基于最小二乘支持向量机(LS - SVM)的非线性系统预测控制算法。
Applying high order cumulants and support vector machines (SVM), an algorithm is proposed for automatic recognition of digital communication signals.
针对数字信号调制模式识别问题，提出了运用高阶累积量和二叉树支持向量机(SVM)进行自动识别的算法。
The foundations of support vector machines are introduced. An evaluation model based on SVM is made, and the model is tested to obtain better results.
介绍了支持向量机的基本思想，提出了一个基于支持向量机的粮虫模式识别系统。
Support Vector Machines(SVM) is a potential hyperspectral remote sensing classification method because it is advantageous to deal with problems with high dimensions, small samples and uncertainty.
支持向量机因其适用高维特征、小样本与不确定性问题的优越性，是一种极具潜力的高光谱遥感分类方法。
By taking Xianyou County as an example, a new method for landslide hazard evaluation based on GIS and Support Vector Machines (SVM) is presented in this paper.
以仙游县为例，探讨了将地理信息系统技术(GIS)和支持向量机(SVM)算法应用于滑坡灾害危险性评价的基本思路和技术路线。
The paper presents a method of Chinese chunk recognition based on Support Vector Machines (SVM) and transformation-based error-driven learning.
本文研究了一种支持向量机(SVM)和基于转换的错误驱动学习相结合的汉语组块识别方法。
Support Vector Machine (SVM) is a kind of learning machines constructed according to SRM principle on the basis of VC theory, which is much more powerful man the neural networks.
支撑矢量机（SVM）是在VC理论的基础上根据结构风险最小归纳原理建立的一种比神经网络更强有力的学习机。
A method of object's performance classification based on Rough Set (RS) and Support Vector Machines (SVM) was proposed and it classifies the object's performance by composing the RS and SVM.
提出了一种基于粗糙集(RS)和支持向量机(SVM)的目标对象的性能分类方法，该方法将RS和SVM结合在一起对性能进行分类。
Uniform design and Least Square Support Vector Machines (LS-SVM) were applied to optimize design parameters of capacitance tomography sensors in this paper.
提出一种采用均匀设计与最小二乘支持向量机相结合的电容层析成像传感器结构参数优化方法。
This paper presentes the characteristics, properties and relationship of Covering Algorithms and the kernel function of Support Vector Machines (SVM) firstly.
该文首先介绍了构造型神经网络中的覆盖算法的特点和性质，以及与支持向量机(SVM)中的核函数法的关系。
The SVM (support vector machines) is a classification technique based on the structural risk minimization principle.
是一种基于结构风险最小化原理的分类技术。
After studying on modeling theories of SVM and the parameter optimization of SVM, the Least Squares Support Vector Machines tool LSSVM.
在研究支持向量机的建模理论和参数优化方法的基础上，将最小二乘法支持向量机工具LSSVM。
Rolling Bearing Status Monitoring method based on Support Vector Machines (SVM) is presented.
提出了一种基于支持向量机的滚动轴承状态监测方法。
Support Vector Machines(SVM) are developed from the theory of limited samples Statistical Learning Theory (SLT) by Vapnik et al. , which are originally designed for binary classification.
支持向量机（SVM）是建立在统计学习理论基础上的一种小样本机器学习方法，用于解决二分类问题。
In this paper we propose a blind super-resolution image restoration algorithm based on Support Vector Machines (SVM).
本文提出了一种基于支撑向量机的盲超分辨率图像复原算法。
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