Risk evaluation of power system communication based on PCA and RBF neural network

被引：0

作者：

Huisheng Gao ^{[1
]}

Jianmin Fu ^{[1
]}

机构：

[1] N China Electr Power Univ, Dept Elect & Commun Engn, Baoding 071003, Peoples R China

来源：

ICIEA 2007: 2ND IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-4, PROCEEDINGS | 2007年

关键词：

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Based on principal component analysis (PCA) and radial basic function (RBF) neural network (NN), this paper proposes an approach to evaluate the risk of power system communication, in which the complexity of influencing factor and difficulty to describe evaluation in models of mathematics is overcome. Concretely, the original input space is reconstructed by principal component analysis(PCA) and the structure of the network is determined according to the contributions from the principal components respectively, so the ability of training speed and evaluation are improved. The effectiveness of the proposed algorithm is verified by the practical data for the power system communication.

引用

页码：731 / 736

页数：6

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