|本期目录/Table of Contents|

[1]王艳,陈欢欢,沈毅,等.有向无环图的多类支持向量机分类算法[J].电机与控制学报,2011,(04):85-89.
 WANG Yan,CHEN Huan-huan,SHEN Yi.Multi-class support vector machine based on directed acyclic graph[J].,2011,(04):85-89.
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
期数:
2011年04
页码:
85-89
栏目:
出版日期:
2011-05-10

文章信息/Info

Title:
Multi-class support vector machine based on directed acyclic graph
作者:
王艳; 陈欢欢; 沈毅;
哈尔滨工业大学航天学院;
Author(s):
WANG Yan; CHEN Huan-huan; SHEN Yi
School of Astronautics; Harbin Institute of Technology; Harbin 150001; China
关键词:
支持向量机 有向无环图 分离性测度 故障诊断
Keywords:
support vector machine directed acyclic graph separability measure fault diagnosis
分类号:
TP18
DOI:
-
文献标志码:
A
摘要:
为研究基于有向无环图的支持向量机分类算法以及在故障诊断问题中的应用,考虑到有向无环图的结构运算相当于一个表操作,且分类结果依赖于有向无环图中节点的排列顺序,提出一种分类算法,该算法引入基于类分布的类间分离性测度,估计各类训练数据间的分布性质,建立初始操作表单,将样本所有可能的类别按照一定顺序排列在表单中,从而重新组合有向无环图中的节点顺序,构造基于分离性测度的有向无环图的拓扑结构。通过对3个典型数据集的数值仿真研究,结果表明所提算法的性能优于传统算法。
Abstract:
Support vector machine based on directed acyclic graph(DAG) was proposed for multi-class classification and applied to multi-class fault diagnosis problems.Considering DAG being equivalent to a list operation,and the classification performance depending on the nodes’ sequence in the graph,a classification measure based on the distribution of multi-class data was introduced.This method used separability measure between class to estimate distribution character of each class,established the initialization oper...

参考文献/References:

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备注/Memo

备注/Memo:
国家自然科学基金(61071182,60874054); 高等学校博士学科点专项科研基金(20092302110037)
更新日期/Last Update: 2011-11-07