研究基于模糊系数规划的模糊支持向量分类机。
Research on the fuzzy SVMs based on fuzzy coefficient programming.
论文研究模糊支持向量分类机在冠心病诊断中的应用。
In this paper, we have studied on applying fuzzy support vector classification to coronary heart diagnose.
并且分别详尽的阐述了支持向量分类和支持向量回归的理论思想、计算步骤和优化算法。
It also elaborates the ideas, counting steps and optimize algorithm of support vector classification and regression.
给出带有模糊决策的模糊机会约束规划模型，在此基础上，研究模糊线性支持向量分类机(算法)和模糊线性支持向量回归机(算法)。
Proposed the model of fuzzy chance constrained programming with fuzzy decision, and did some research on fuzzy linear support vector regression (algorithm) on this base.
大部分数字识别的工作可以由神经网络来完成，但最近支持向量机也被证明可以在分类方面做得更好。
Much of the work on digit recognition has been done in the neural network community, but more recently support vector machines have proven to be even better classifiers.
本文首次采用支持向量机方法对医学图像进行了分类研究。
This paper firstly investigates the application of support vector machines for medical image classification.
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.
采用小波多分辩率分析方法提取基因表达的特征，利用支持向量机和BP神经网络方法进行分类。
The features of gene expression are extracted by the wavelet multi-resolution analysis, the features are classified by the support vector machines and BP neural network methods.
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.
在此基础上，研究了用球结构支持向量机作分类器，对滚动轴承内圈故障的劣化程度进行识别的理论和方法。
Basing on these, study theory and method of using Sphere-structured Support Vector Machines to recognize the roll bearing inside track's fault deterioration extent.
实验结果表明，采用支持向量机方法进行变异语音分类是可行的。
Experimental results indicate that it is feasible to adopt SVMs for stressed speech classification.
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。
The last topic is about a trainable object detection system using at its core a Support Vector Machine classifier.
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.
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。
Recently, Support Vector Machine is well applied in pattern recognition, function approximate, data mining and text auto categorization.
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。
We also discussed the application of support vector machine in multivariate classification with some examples.
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。
This article presents a new method of plant classification of iris based on the support vector machine classification principle.
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.
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.
基于非平衡数据集的支持向量域分类模型，提出了一种银行客户个人信用预测方法。
A new predication method of customer credit of Banks is proposed based on the support vector domain classification model of non-balance data set.
该文介绍了一种文本过滤算法，该算法把基于空间向量模型的主题分类算法与基于支持向量机文本态度分类结合起来。
This paper introduces a text filtering system merging topic classification based on vector space model and sentiment classification based on support vector machine.
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.
然后基于支持向量机算法构造了支持向量机分类器，将其用于心电图分类，取得了较高的准确率。
Then a support vector machine classifier is constructed and applied to ECG classification. Comparing with the classification of ECG by eyes, the classification results is much more precise.
介绍了支持向量机分类和回归算法，将其应用于梁结构的损伤诊断中。
This paper introduces the support vector classification and regression algorithms, which are applied to the structure damage identification.
为了将一般增量学习算法扩展到并行计算环境中，提出一种基于多支持向量机分类器的增量学习算法。
In order to extend common incremental learning algorithms into a parallel computation setting, an incremental learning algorithm with multiple support vector machine classifiers is proposed.
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.
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.
同时本文将机器学习和相关反馈结合起来用于图像检索，在实验中使用了K -NN、BP神经网络和支持向量机分类器。
At the same time, we used relevance feedback and machine learning used in image retrieval. K-NN, BP neural network and support vector machine classifiers were used in experiments.
同时本文将机器学习和相关反馈结合起来用于图像检索，在实验中使用了K -NN、BP神经网络和支持向量机分类器。
At the same time, we used relevance feedback and machine learning used in image retrieval. K-NN, BP neural network and support vector machine classifiers were used in experiments.
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