提出了一种基于相空间重构与支持向量机预测滑坡位移的新方法。
We presented a novel method for forecasting landslide displacement based on phase space reconstruction and support vector machine.
将粗糙集与支持向量机两者结合，并建立了基于粗糙集——支持向量机的混合预测模型。
And combining rough set and support vector machine, the mixture prediction model is established based on rough set and support vector machine.
提出依存关系规则与统计方法相结合，实现了基于依存关系与支持向量机的问题分类机制。
The results show that the feature extraction method using SVM based on dependency relations can get high classification accuracy.
同时将内模控制与支持向量机逆辨识结合，提出支持向量机内模控制（SVM—IMC）。
Combining the IMC with the identification of inverse-model, the internal model controller of SVM (SVM-IMC) is proposed.
为了系统地归纳统计学习理论与支持向量机的基本思想和算法，总结目前该领域的最新研究成果。
The basic statistical learning theory (SLT) and its corresponding algorithms, support vector machines (SVMs), are surveyed, and especially, its latest research results are summarized and studied.
结合核主元分析与支持向量机的特点，提出了一种基于核主元分析与支持向量机的人脸识别方法。
By integrating the characteristics of KPCA and SVM, a face recognition method based on these two algorithms is presented.
为了系统地归纳统计学习理论与支持向量机的基本思想和算法，总结目前该领域的最新研究成果。
Support vector machine is a new learning machine, and it is based on the statistics learning theory.
为了系统地归纳统计学习理论与支持向量机的基本思想和算法，总结目前该领域的最新研究成果。
Support vector machine is a new machine learning algorithm, based theoretically on statistic learning theory created by Vapnik.
提出了一种红外热像处理与支持向量机多值分类器相结合的新方法对高压绝缘子污秽等级进行检测。
This paper presents a new method that integrates infrared thermal image technique with support vector machine (SVM) classifiers to check the contamination grades of high voltage insulators.
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.
首先概述了本文研究内容的基础—统计学习理论与支持向量机方法，为本文后续的研究方向和内容进行了铺垫。
This paper's basic concepts of Statistical Learning Theory and SVM are summarized firstly, which are the groundwork of next research works.
该文首先介绍了构造型神经网络中的覆盖算法的特点和性质，以及与支持向量机(SVM)中的核函数法的关系。
This paper presentes the characteristics, properties and relationship of Covering Algorithms and the kernel function of Support Vector Machines (SVM) firstly.
粗糙集理论(rst)与支持向量机(SVM)作为模式识别，数据处理的有效工具，已成为机器学习的研究热点。
As an effect tool of pattern recognition and data processing, rough set theory (RST) and support vector machine (SVM) have become the focus of research in machine learning.
现有的分类预测的方法有许多种，常见的有决策树算法(C4.5)、贝叶斯分类算法、BP算法与支持向量机等。
There are many classification methods to forecast such as decision tree algorithm (C4.5), Bayes algorithm, BP algorithm and SVM.
利用隐马尔克夫模型与支持向量机相结合，对站立和行走过程中的下肢表面肌电信号进行分类，用来控制多功能假肢。
Classifying myoelectric signals using hidden Markov model and support vector machine to process myoelectric signals, with the task of discrimination five classes of multifunction prosthesis movement.
这堂课我们将讨论且提出有关支持向量机和调控网络建构与选择适当的核心函式运作的一些结果和问题。
In this class we discuss some results and open problems related to the construction and choice of the appropriate kernel functions for Support Vector Machines and Regularization Networks.
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.
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.
利用支持向量机表达地基承载力与地基参数之间的非线性映射关系，在此基础上计算地基的承载力。
Support vector machine represented the nonlinear relationship between parameter of foundation and foundation bearing capacity, and compute the foundation bearing capacity based on this relationship.
与统计分析和神经网络相比，基于结构风险最小的支持向量机有更好的分类性能。
Compared with multivariate statistics and artificial neural networks, support vector machine based on structure risk minimization has better classification performance.
将改进的支持向量回归机与B -样条网络相结合，提出了一种建立回归曲线模型的新算法。
A new algorithm for modeling regression curve is put forward in the paper, it combines B-spline network with improved support vector regression.
为了提高性别检测的精度，提出了一种支持向量机(SVM)与主动外观模型(aam)相结合的迭代学习算法。
In order to increase accuracy in gender classification, an iterative learning approach combining support vector machine (SVM) and active appearance model (AAM) was proposed.
在有限元模拟基础上，采用正交设计与最小二乘小波支持向量机对充液拉深过程参数优化进行了研究。
Orthogonal design and least squares wavelet support vector machine are integrated to optimize the technological parameters of hydro-mechanical deep drawing process using FEM.
基于逆系统控制思想，提出一种支持向量机(SVM)直接逆控制与PID控制相结合的复合控制策略。
Based on the thought of inverse system control, a composite strategy was proposed, which combines direct inverse control based on support vector machine (SVM) with PID control.
支持向量机因其适用高维特征、小样本与不确定性问题的优越性，是一种极具潜力的高光谱遥感分类方法。
Support Vector Machines(SVM) is a potential hyperspectral remote sensing classification method because it is advantageous to deal with problems with high dimensions, small samples and uncertainty.
为了找出PET产品的聚酯粘度检测的操作条件与质量指标之间的关系，采用支持向量机对聚酯粘度进行软测量建模。
For finding the relationship of operation conditions and index of quality, support vector machine is used for modeling the PET conglutination.
我们将讨论拔靴集成法与多模激发法，以及这两个演算法是如何成功的被运用。我们也将介绍近来运用与拔靴集成法相似的方法，结合支持向量机所做的一些案例。
We discuss bagging and boosting and suggest some plausible justification for their success. We also describe some recent work about combining SVMs in a way similar to bagging.
首先，将支持向量机和混合推理选做系统预警与诊断功能适用的方法。
Firstly, choose the Support Vector Machine and the forward and backward reasoning as methods for the financial distress warning and the financial diagnosis.
首先，将支持向量机和混合推理选做系统预警与诊断功能适用的方法。
Firstly, choose the Support Vector Machine and the forward and backward reasoning as methods for the financial distress warning and the financial diagnosis.
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