进而提出了基于支持向量机(SVM)的网络延时预测方法。
The prediction method of network delays based on support vector machine (SVM) was put forward.
支持向量机（SVM）是根据统计理论提出的一种新的学习算法。
The support vector machine(SVM) is a new learning technique based on the statistical learning theory.
本文主要研究目前较为流行的基于统计学习理论的分类方法——支持向量机方法(SVM)，以及小波变换提取特征的方法，将其用于人脸检测。
This paper mainly make research on classify methods based on statistical theory, support vector machine (SVM), and feature extraction method-wavelet transform, and using them in human face detection.
提出了一种基于最小二乘支持向量机(LS - SVM)的铁路客运量预测的新方法。
A new prediction approach for railway passenger volume is put forward by means of Least Squares Support Vector Machine (LS-SVM).
目的：探讨带先验知识的支持向量机（P-SVM）数据挖掘算法在中医证候信息自动分类中的应用。
The paper explores possible applications of Prior knowledge Support Vector Machine (P-SVM) based data mining algorithm in an automatic TCM syndrome classification system.
论文将支持向量机引入到动态电能质量分类问题中。
This paper presents a Support Vector Machine (SVM) method for classification of dynamic power quality disturbances.
提出了一种最小二乘支持向量机的电池剩余电量预测新模型。
A novel prediction model for remaining capacity of batteries based on least square support vector machine (LS-SVM) was proposed.
文章中讨论支持向量机与基础追踪去杂讯法之间的关系。
This is the paper in which the relation between SVM and BPD is studied.
本文基于混合学习和集成学习的思想，将这两种方法应用于支持向量机建模技术中，主要解决预测分析问题。
This paper mainly focuses on the prediction problem by the application of hybrid and ensemble thinking into the modeling base on SVM.
模型选择是支持向量机一个重要的研究方向。
仿真研究表明，SVM具有优良的逆模型辨识能力，基于模糊控制补偿的支持向量机逆控制系统的动态性能好、跟踪精度高、鲁棒稳定性强。
Simulations demonstrate that SVM has good nonlinear approximation capability for inverse model, and the proposed control system has good dynamic and static performances as well as good robustness.
支持向量机(SVM)是一种新的通用学习机器，它从结构风险最小化的角度，分析了学习过程的一致性、收敛速度等。
Support vector machine (SVM) is a new general learning machine, which analyzes the consistency of learning and speed of convergence from structure risk minimization principle.
还讨论支持向量机用于人脸识别的主要处理流程和识别框图。
It also discusses the primary processing and recognition diagram of SVM applied to face recognition.
支持向量机(SVM)是一种新型的机器学习方法。
Support vector machine (SVM) is a new machine learning technique.
首先利用色度矩提取植物病害叶片的特征向量，然后利用支持向量机分类方法进行病害的识别。
At first extracting features of chromaticity moments was done then classification method of SVM for recognition of plant disease was discussed.
支持向量机是一种基于统计学习理论的新型机器学习方法，它可以被广泛地用于非线性系统建模。
Support vector machine (SVM) is a brand-new machine learning technique based on statistical learning theory. It is an ideal facility for modeling of various nonlinear systems.
支持向量机(SVM)是基于统计学习理论的新一代机器学习技术。
Support vector machine (SVM) is a new generation machine learning technique based on the statistical learning theory.
然后基于支持向量机进行分类建模和预测过程。
Then, we implement classification modeling and forecast based on SVM.
论文将支持向量机的机器学习方法引入到医学图像的分类问题。
In this thesis, SVM as a new machine learning method is brought into medical image classification.
针对玉米病害叶片彩色纹理图像的特点，提出一种将支持向量机和色度矩分析应用于玉米病害识别的方法。
According to the features of color texture image of maize disease, a method of recognizing disease by using support vector machine (SVM) and chromaticity moments is introduced.
提出一种基于聚类分析和支持向量机(SVM)的布匹瑕疵分类方法。
Presents an efficient method of fabric defect classification based on cluster analysis and support vector machine (SVM).
给出了一种基于支持向量机的数字调制信号分类器设计方法。
A classification method based on Support Vector Machine (SVM) is given in the digital modulation signal classification.
目的探讨支持向量机在基因表达数据分类研究中的应用条件和效果。
Objective Discuss the condition and the effect of SVM in the classification of gene expression data.
核函数是SVM的关键技术，核函数的选择将影响着支持向量机的学习能力和泛化能力。
Kernel function is the key technology of SVM, the choice of kernel will affect the learning ability and generalization ability of SVM.
这一方法大大提高了支持向量机分类的泛化能力，从而大大提高了支持向量机的应用范围。
This approach greatly improves the generalization ability of SVM classification and its application area is extended.
在分析支持向量机原理的基础上，对支持向量机近年来在羽绒识别中的应用进行了综述和探讨。
The paper reviews the principles of SVM and then overviews of its application research on feather and down category recognition is mainly talked about.
提出了一种利用支持向量机(SVM)对机械系统故障进行分类的新方法；以二值分类为基础，开发了基于支持向量机的多值分类器。
A new method of fault classification for mechanical system by means of support vector machine (SVM) is proposed and a multi-class SVM classifier based on binary classification was developed.
支持向量机是一种基于统计学习理论的新型机器学习方法。
Support vector machine (SVM) is a new learning machine based on the statistical learning theory.
为了解决支持向量机的分类仅应用于较小样本集的问题，提出了一种密度聚类与支持向量机相结合的分类算法。
To solve the problem that support vector machine(SVM) can only classify the small samples set, a new algorithm which applied SVM to density clustering is proposed.
为了解决支持向量机的分类仅应用于较小样本集的问题，提出了一种密度聚类与支持向量机相结合的分类算法。
To solve the problem that support vector machine(SVM) can only classify the small samples set, a new algorithm which applied SVM to density clustering is proposed.
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