To check for compatibility, run the command grep vmx /proc/cpuinfo (on AMD, run the command grep svm /proc/cpuinfo).
为了检查兼容性，请运行命令grepvmx /proc/cpuinfo（对于 AMD，运行命令 grep svm /proc/cpuinfo）。
This file specifies whether the VMX (Intel) or SVM (AMD) extensions are supported.
这个文件指定了是否支持vmx (Intel)或svm (amd)扩展。
The SVM saves all information about structures of volumes on a disk area called the replica.
SVM将有关卷结构的所有信息都保存在一个称为副本(replica)的磁盘区中。
SVM provides you with the ability to manage large number of disks, and it also improves data availability.
SVM为您提供管理大量磁盘的能力，同时可以改进数据的可用性。
The SVM state database stores configuration and states information about volumes, including hot spares and disk sets.
SVM状态数据库存储有关卷的配置和状态信息，包括热备份磁盘 (hot spares) 和磁盘集。
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。
This paper presents an instrument recognition method based on SVM.
文章提出了一种基于支持向量机的乐器识别方法。
Then, we implement classification modeling and forecast based on SVM.
然后基于支持向量机进行分类建模和预测过程。
The torque ripple could be significantly reduced by SVM-based DTC scheme.
基于SVM的DTC方案可以有效地减小转矩波动。
Then, we realize classification modeling and forecasting test based on SVM.
然后基于支持向量机进行分类建模和预测。
SVM for text classification - tutorial on machine learning? How do I get started?
SVM文本分类的机器学习教程？我如何开始？
RASVM can obtain higher performance than the standard SVM in the stock prediction.
在股票预测中RASVM能够获得比标准的SVM更高的性能。
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。
To improve the recall, an excursion factor is used in the procedure in which SVM is constructed.
在构造支持向量机的过程中，为了提高分类的召回率，采用了一种偏移因子。
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。
It also discusses the primary processing and recognition diagram of SVM applied to face recognition.
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。
Objective Discuss the condition and the effect of SVM in the classification of gene expression data.
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。
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。
SVM is a novel powerful machine learning method developed in the framework of Statistical Learning Theory (SLT).
支持向量机是在统计学习理论基础上开发出来的一种新的、非常有效的机器学习方法。
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。
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。
SVM based inverse model of nonlinear system is used as feed-forward controller to form direct inverse model controller.
由SVM辨识的逆模型作为前馈控制器，形成直接逆模型控制器。
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。
Support Vector Machine (SVM) can be used to solve classification problems, and it is very important to optimize its parameters.
支持向量机(SVM)可以很好地用来解决分类问题，参数优化尤其重要。
The SVM not only controls the complexity of the machine learning, but also has nice convergence speed and generalizing ability.
这种方法从理论上控制了机器学习的复杂性，同时具有良好的收敛速度和推广能力。
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。
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。
Due to its complete theoretical basis as well as excellent performance, SVM has become a hotspot in the area of pattern recognition.
由于具有完备的理论基础和良好的性能，支持向量机已经成为模式识别的一个研究热点。
This paper mainly focuses on the prediction problem by the application of hybrid and ensemble thinking into the modeling base on SVM.
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。
Kernel function is the key technology of SVM, the choice of kernel will affect the learning ability and generalization ability of SVM.
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。
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