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。
Automatic video caption location based on support vector machine.
基于支持向量机的视频字幕自动定位方法。
The applications of support vector machine are reviewed in DNA microarray.
就支持向量机在DNA微阵列的应用做一综述。
A laser welding quality monitoring method is proposed, based on support vector machine.
提出了一种基于支持向量机的激光焊接质量监测方法。
Validating the effectiveness of support vector machine for handwritten digit recognition.
验证支持向量机用于手写数字识别的有效性。
This paper studies a plane image recognition algorithm based on Support Vector Machine (SVM).
研究了一种基于支持向量机的飞机图像识别算法。
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。
A new method for modulation classification based on Support Vector Machine (SVM) is presented.
提出一种基于支持向量机的实际调制信号自动识别新方法。
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。
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。
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。
Support vector machine constructs an optimal hyperplane utilizing a small set of vectors near boundary.
支持向量机利用接近边界的少数向量来构造一个最优分类面。
A new method of infrared spectrum analysis based on support vector machine for mixture gas was proposed.
介绍了一种基于支持向量机的混合气体红外光谱组分浓度和种类分析的新方法。
In order to solve the problem, support vector machine based on weighted feature is proposed in this paper.
为了解决这个问题，本文提出了一种基于特征加权的支持向量回归机。
Therefore it is of great significance to study the properties of kernel function of support vector machine.
因此研究支持向量机的核函数性质，对于寻找核函数有重要意义。
We also discussed the application of support vector machine in multivariate classification with some examples.
还对支持向量机在多元分类中的应用进行了讨论，并给出了实例。
The last topic is about a trainable object detection system using at its core a Support Vector Machine classifier.
最后一个主题将讲解支持向量机分类物中核心使用的可训练物件侦测系统。
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。
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。
The support vector machine based speaker verification models are trained on the enrolled speaker and the background model.
支持向量机用作说话人确认模型来训练目标说话人和背景说话人的语音数据。
Transductive inference based on support vector machine is a relatively new research region in statistical learning theory.
基于支持向量机的直推式学习是统计学习理论中一个较新的研究领域。
Multiple support vector machine can perform more complex tasks because every support vector machine only finish the subtask.
由于每个子网络只完成相应的子任务，因而多支撑向量网络可以解决更为复杂的学习任务。
This article presents a new method of plant classification of iris based on the support vector machine classification principle.
提出了基于支持向量机的分类原理对鸢尾属植物进行分类的方法。
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。
Recently, Support Vector Machine is well applied in pattern recognition, function approximate, data mining and text auto categorization.
目前，支持向量机在模式识别、函数逼近、数据挖掘和文本自动分类中均有很好的应用。
The results indicate that the support vector machine possesses extensive application prospects in processing earthquake precursory data.
研究结果表明，支持向量机方法在地震前兆数据处理中有着广泛的应用前景。
Applied support vector machine to foundation engineering, and proposed support vector machine method to compute the foundation bearing capacity.
将支持向量机方法应用到地基工程中，提出了计算地基承载力的支持向量机方法。
The fuzzy judgment support vector machine algorithm based on loss function is proposed, and compared with fuzzy sample support vector machine algorithm.
提出了基于损失函数的模糊判决支持向量机算法，并与模糊样本支持向量机算法进行了比较。
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