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.
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 machine learning technique.
支持向量机(SVM)是一种新型的机器学习方法。
The prediction method of network delays based on support vector machine (SVM) was put forward.
进而提出了基于支持向量机(SVM)的网络延时预测方法。
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。
The support vector machine(SVM) is a new learning technique based on the statistical learning theory.
支持向量机（SVM）是根据统计理论提出的一种新的学习算法。
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.
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。
Support vector machine (SVM) is a new generation machine learning technique based on the statistical learning theory.
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。
A new prediction approach for railway passenger volume is put forward by means of Least Squares Support Vector Machine (LS-SVM).
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。
The paper explores possible applications of Prior knowledge Support Vector Machine (P-SVM) based data mining algorithm in an automatic TCM syndrome classification system.
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。
This paper presents a Support Vector Machine (SVM) method for classification of dynamic power quality disturbances.
论文将支持向量机引入到动态电能质量分类问题中。
A novel prediction model for remaining capacity of batteries based on least square support vector machine (LS-SVM) was proposed.
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。
Secondly, summarize the application of the machine learning methods in the bioinformatics and expatiate on the rationale of the Support Vector Machine (SVM).
总结归纳了机器学习方法在目前生物信息学的应用，并对支撑向量机（SVM）算法的基本原理做了阐述；
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.
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 plant disease, recognition of plant disease using support vector machine (SVM) and chromaticity moments was introduced.
针对植物病害彩色纹理图像的特点，提出将支持向量机和色度矩分析方法相结合应用于植物病害识别中。
Presents an efficient method of fabric defect classification based on cluster analysis and support vector machine (SVM).
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。
Support Vector Machine (SVM) is an important learning method of statistical learning theory, and is also a powerful tool for pattern recognition.
支持向量机是统计学习理论的一个重要学习方法，也是解决模式识别问题的一个有力工具。
A novel evaluation method of customer satisfaction degree (CSD) in logistics based on support vector machine (SVM) was presented.
提出了一种新的基于支持向量机(SVM)的物流服务顾客满意度(CSD)评价方法。
The selection of the kernel function parameter and error penalty factor affected the precision of the support vector machine (SVM) significantly.
核函数参数和误差惩罚因子的选择对支持向量机模型（SVM）的精度有较大影响。
This paper proposes a new Support Vector Machine(SVM) for anomaly intrusion detection method based on Latent Semantic Indexing(LSI).
论文提出了一种基于潜在语义索引（LSI）和支持向量机（SVM）的异常入侵检测方法。
Support vector machine (SVM) is a new learning machine based on the statistical learning theory.
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。
So a novel promising machine learning technique specifically developed for analyzing little amount of samples, SVM (Support Vector Machine), will be more suitable in practical industrial application.
因此在实际的工程应用中，支持向量机（SVM）作为一种新型的小样本建模分析工具是更适合的。
The support vector machine (SVM) is an algorithm based on structure risk minimizing principle and high generalization ability.
支持向量机(SVM)是一种基于结构风险最小化原理，具有很好推广性能的学习算法。
With an analysis of the estimation of cigarettes tar content, an estimation method is proposed based on Support Vector Machine (SVM).
分析了卷烟焦油含量预测问题，提出了基于支持向量机的卷烟焦油含量预测方法。
A classification method based on Support Vector Machine (SVM) is given in the digital modulation signal classification.
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 network traffic anomaly detection mechanism is presented based on support vector machine (SVM).
提出了一种基于支持向量机的网络流量异常检测方法。
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。
Subsequently those preprocessing data are the input of SVM (support vector machine) algorithm, which is used for ball bearing fault detection.
将预处理后数据作为SVM(支持向量机)算法的输入，通过SVM算法来检测轴承故障。
Furthermore, combined with the nearest distance classifier, the support vector machine (SVM) is used for classification.
然后再以支持向量机(SVM)和最近邻分类法相结合组成分类器进行分类。
Furthermore, combined with the nearest distance classifier, the support vector machine (SVM) is used for classification.
然后再以支持向量机(SVM)和最近邻分类法相结合组成分类器进行分类。
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