1)MSVM多元支持向量机
1.For overcoming the difficulty of leak detection for hot oil pipeline under complicated conditions,a method based on MSVM(Multi-Support Vector Machine)is proposed and the diagnosis model is established.针对复杂工况下热原油管道泄漏难以准确识别的难题,提出采用基于多元支持向量机的管道泄漏诊断方法,并建立了识别模型,可以在小样本情形下完成模型的训练工作,实现多种工况下对压力波动信号的分类识别,从而提高评判泄漏的有效性和准确性。
2)TSVM三元支持向量机
3)multiclass SVM多类支持向量机
1.In this paper,a method of decision fusion based on multiclass SVM and D-S evidential theory is presented to try to solve the problem,multiclass SVM is used as the local classifier, and the BPAF is constructed accordingly,then the primary results are fused to obtain the ultima result using D-S evidential theory.本文提出了一种基于多类支持向量机和D-S证据理论的决策融合算法,将多类支持向量机作为局部判决器,构造了相应的基本概率赋值函数,然后用D-S证据理论对各初步判决结果进行融合,得出对目标的最终识别结论。
英文短句/例句
1.Study on Text Classification Based on Multi-class Support Vector Machines;基于多类支持向量机的文本分类研究
2.Research on flatness recognition based on M-SVMs基于多类支持向量机的板形识别方法
3.An Improved Support Vector Machine Based on Binary Tree一种新的二叉树多类支持向量机算法
4.Multi-class SVM method based on non-balanced binary tree非平衡二叉树多类支持向量机分类方法
5.Research on Text Classification Based on Binary Tree Multiclass Support Vector Machines基于二叉树多类支持向量机的文本分类研究
6.Improved Multiclass Classification Methods for Support Vector Machine一种改进的支持向量机多类分类方法
7.A Model of Multiclass Pattern Recognition Based on Support Vector Machine;基于支持向量机的多类模式识别模型
8.Polynomial smooth semi-supervised support vector classifier多项式光滑的半监督支持向量分类机
9.A Sparse Tikhonov Regularized Multi-Class Support Vector Machine稀疏Tikhonov正则化多分类支持向量机
10.Research on Machine Fault Pattern Classification Based on Support Vector Machine基于支持向量机的机械故障多类分类研究
11.Multiclassification Method Research Based on Fuzzy Support Vector Machines;基于模糊支持向量机的多类分类方法研究
12.Study on Classification Methods of Multi-class Mental Tasks Based on Support Vector Machine;基于支持向量机的多类意识任务分类方法研究
13.On the Multi-class Audio Classification Based on the Support Vector Machines;基于支持向量机的多类分类问题的研究
14.The Study and Application of Support Vector Machine Multiclass Classification;支持向量机多类分类算法的研究及应用
15.The Analysis and Design for the Algorithms of Multiclass Classification Based on SVM;支持向量机多类分类算法的分析与设计
16.Multi-class Classification Algorithm Research Based on Fuzzy Support Vector Machines;基于模糊支持向量机的多类分类算法研究
17.Study on Multi-class Classification Method Based on Semi-fuzzy Hypersphere Support Vector Machine;半模糊超球支持向量机多类分类方法研究
18.Research of Multi-calss Text Categorization Method Based on Fuzzy Support Vector Machine基于模糊支持向量机的多类文本分类方法研究
相关短句/例句
TSVM三元支持向量机
3)multiclass SVM多类支持向量机
1.In this paper,a method of decision fusion based on multiclass SVM and D-S evidential theory is presented to try to solve the problem,multiclass SVM is used as the local classifier, and the BPAF is constructed accordingly,then the primary results are fused to obtain the ultima result using D-S evidential theory.本文提出了一种基于多类支持向量机和D-S证据理论的决策融合算法,将多类支持向量机作为局部判决器,构造了相应的基本概率赋值函数,然后用D-S证据理论对各初步判决结果进行融合,得出对目标的最终识别结论。
4)Multi-class Support Vector Machine多类支持向量机
1.Data fusion strategies for small sample based on multi-class support vector machine以多类支持向量机为基础的小样本信息融合策略
2.A new method of image classification based on wavelet transformation and multi-class support vector machine is proposed,which employs wavelet transformation to extract features of the original images and then classifies them by multi-class support vector machine.提出了一种基于小波变换和多类支持向量机的图像分类新方法,该方法利用小波变换进行图像特征提取,利用多类支持向量机进行图像分类,并与基于图像底层特征的图像分类方法进行了实验比较。
5)multi-class SVM多类支持向量机
1.Application of modified wavelet features and multi-class SVM to pathological vocal detection;基于小波特征和多类支持向量机的病态语音识别方法
2.New multi-class SVM algorithm based on one-class SVM;一种新的多类支持向量机算法
3.For indicating the existence and attack intensity of DDoS attack simultaneously,multi-class SVM (MCSVM) is introduced to detecting DDoS Attacks.为了在指示攻击存在的同时,也指示攻击强度,多类支持向量机(MCSVM)被引入到DDoS检测中。
6)multiple support vector machine多支持向量机
1.Monitoring model based on kernel principal component analysis and multiple support vector machines and its application基于核主元分析与多支持向量机的监控诊断方法及其应用
2.Based on the idea that the accuracy of model could be significantly improved by combining several sub-models,a multiple support vector machine(MSVM)modeling approach was proposed to buil.基于多个模型的组合可以提高模型精度和鲁棒性的思想,提出多支持向量机(MSVM)组合模型的软测量建模方法。
延伸阅读
支持向量机方法支持向量机(SVM)是90年代中期发展起来的基于统计学习理论的一种机器学习方法,通过寻求结构化风险最小来提高学习机泛化能力,实现经验风险和置信范围的最小化,从而达到在统计样本量较少的情况下,亦能获得良好统计规律的目的。支持向量机算法是一个凸二次优化问题,能够保证找到的极值解就是全局最优解,是神经网络领域域取得的一项重大突破。与神经网络相比,它的优点是训练算法中不存在局部极小值问题,可以自动设计模型复杂度(例如隐层节点数),不存在维数灾难问题,泛化能力强。
