The Research of Lagrangian Support Vector Machine Based on Flexible Polyhedron Search Algorithm
被引:0
作者:
Chen, YongQi
论文数: 0引用数: 0
h-index: 0
机构:
Ningbo Univ, Sch Sci & Technol, Ningbo 315211, Zhejiang, Peoples R ChinaNingbo Univ, Sch Sci & Technol, Ningbo 315211, Zhejiang, Peoples R China
Chen, YongQi
[1
]
Yang, XiangSheng
论文数: 0引用数: 0
h-index: 0
机构:
Ningbo Univ, Sch Sci & Technol, Ningbo 315211, Zhejiang, Peoples R ChinaNingbo Univ, Sch Sci & Technol, Ningbo 315211, Zhejiang, Peoples R China
Yang, XiangSheng
[1
]
机构:
[1] Ningbo Univ, Sch Sci & Technol, Ningbo 315211, Zhejiang, Peoples R China
来源:
ADVANCES IN COMPUTER SCIENCE, INTELLIGENT SYSTEM AND ENVIRONMENT, VOL 3
|
2011年
/
106卷
关键词:
Lagrangian support vector machine;
flexible polyhedron search algorithm;
fault classification;
D O I:
暂无
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
Parameters selection is important in the research area of support vector machine. Based on flexible polyhedron search algorithm, this paper proposes automatic parameters selection for Lagrangian support vector machine. An equipment fault classification illustrates that lagrangian support vector machine based on particle swarm optimization has fine classification ability.