|Table of Contents|

Parameter Optimization of Support Vector Machine Based on Ant Colony Optimization Algorithm

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2009年04期
Page:
464-468
Research Field:
Publishing date:

Info

Title:
Parameter Optimization of Support Vector Machine Based on Ant Colony Optimization Algorithm
Author(s):
ZHANG Bei-lin12QIAN Lin-fang1CAO Jian-jun2REN Guo-quan2
1.School of Mechanical Engineering,NUST,Nanjing 210094,China;2.Department of Artillery Engineering of Ordnance Engineering College,Shijiazhuang 050003,China
Keywords:
ant colony optimization algorithm support vector machine parameter optimization oil analysis fault diagnosis
PACS:
TP18
DOI:
-
Abstract:
Parameters of support vector machine is the key factor that impacts its classifying performance.A parameter optimization method for support vector machine using ant colony optimization algorithm is discussed.A parameter optimization model is established.The continuous ant colony optimization method based on gridding partition is given and used to resolve the optimization model.The classifying performance reaches the best state by optimizing the penalty factor and the radial basis function.The validity of the method is tested by simulation and application instances,and more than 95% classified right rate is obtained.

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Last Update: 2012-11-19