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基于支持向量机和神经网络对分类问题的比较研究
引用本文:张金会,何政军,田希.基于支持向量机和神经网络对分类问题的比较研究[J].机械工程师,2012(8):31-32.
作者姓名:张金会  何政军  田希
作者单位:1. 华北电力大学机械工程系,河北保定,071003
2. 华北电力大学动力工程系,河北保定,071003
摘    要:支持向量机(SVM)和神经网络(ANN)是模式识别的两种方法,支持向量机是新兴的一种效率更高的识别方法,能够达到比神经网络更好的分类效果。文中以二分类为例比较了二者的分类准确率和效率问题。

关 键 词:支持向量机  神经网络  模式识别

The Comparative Study of Classification Based on Support Vector Machines and Neural Networks
ZHANG Jin-hui , HE Zheng-jun , TIAN Xi.The Comparative Study of Classification Based on Support Vector Machines and Neural Networks[J].Mechanical Engineer,2012(8):31-32.
Authors:ZHANG Jin-hui  HE Zheng-jun  TIAN Xi
Affiliation:(Department of Mechanical Engineering, North China Electric Power University, Baoding 071003, China)
Abstract:Support Vector Machine(SVM) and neural network (ANN) are the two methods of pattern recognition, support vector machines is more efficient identification method which can achieve better classification results than the neural network. Taking two classification as an example, both classification accuracy and efficiency issues are compared.
Keywords:support vector machine  neural network  pattern recognition
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