多类SVM分类算法的研究

支持向量机(Support Vector Machine,SVM)是上世纪九十年代提出的一种基于小样本的新的统计学习方法,较好地解决了非线性、高维数、局部极小点等实际问题.文中分析了SVM基础理论并总结了目前存在的基于支持向量机的主要分类方法,包括一对多方法、一对一方法、决策有向无环图方法、基于二叉树的多类分类方法和其它方法,并对各自的优缺点及性能做了比较.     

基于SVM的汉语动词短语识别

支持向量机(Support Vector Machines,SVM)是一个很有前途的分类新技术。本将支持向量机应用到汉语短语识别中,提出了一种基于支持向量机的汉语动词短语自动识别算法的设计与实现,和传统的基于规则的方法相比取得了比较满意的结果。     

最小二乘支持向量机对数据点的B样条拟合

讨论了基于"结构风险"意义下用最小二乘支持向量回归机构造B样条曲面的逼近问题,其出发点是最小化结构风险,在理论上保证了较好的推广能力,能够实现对原始曲面的逼近;建立了B样条曲面拟合的数学模型,构造了一种特殊的核函数来保证曲面的B样条表示形式.     

Data fusion for fault diagnosis using multi-class Support Vector Machines

INTRODUCTION The failure of machinery reduces the productionrate and increases the costs of production and maintenance.Therefore,it is important to reduce maintenance costs and prevent unscheduled downtimes fomachinery.So knowledge of what,where and howfaults occur is very important.Condition-basedmaintenance(CBM)has the potential to decreaselife-cycle maintenance costs,increase operationareadiness and improve safety.Fault detection andfailure mode diagnosis are also necessary for implem…     

支持向量机在多氯代二苯并呋喃logKow中的应用

应用G98W程序包中的量子化学密度泛涵（DFT）方法,在B3LYP／6—31G（d）水平上,对51种二苯并呋喃及其衍生物（PCDFs）进行几何构型全优化。优化后所得分子的最高占据轨道能量、二苯并呋喃环上1,2,3,7四个原子静电荷密度作为PCDFa分子结构描述符。应用支持向量机构建多氯代二苯并呋喃logKow的定量构效（QSAR）关系模型,所建模型的预测值与实验值吻合的很好,经留一交叉校检法检验该模型,该模型具有良好的稳健性,有一定的应用价值．     

基于分类树和支持向量机的个人信用评估方法

通过对分类树和支持向量机这两种方法在个人信用评估领域的适用性分析,提出了一种将分类树和支持向量机结合起来处理个人信用评估的新方法．用该方法处理含有混合数据的个人信用评估实例,结果表明,该方法有效地提高了整个模型的训练精度和测试精度．     

Nonlinear decoupling controller design based on least squares support vector regression

INTRODUCTION Most practical systems are multivariate nonlin- ear systems. In general, the MIMO (multiple inputs and multiple outputs) systems are coupled. This cou- pling affects the effectiveness of a specific loop con- troller on the corresponding output, and in some case, may become serious and cause many difficulties to the control system design. How to decouple the mul- tivariate systems and design practical controllers is one of the major issues in nonlinear control area. In recen…     

Predictive control of a class of bilinear systems based on global off-line models

INTRODUCTION Bilinear systems are a kind of important nonlinear systems with relatively simple structure, and many industrial processes can be described as a bilinear system. Thus research on the control of this kind of systems is very important. On the other hand, model predictive control (MPC) (Clarke et al., 1987) has been widely used in industrial applications and many predictive control methods focusing on bilinear systems are emerging (Bloemen et al., 2001; Fontes et al., 2004; He…