Application of radial basis function neural network for differential relaying of a power transformer

被引：37
|
作者：
Moravej, Z [1 ]
Vishwakarma, DN [1 ]
Singh, SP [1 ]
机构：
[1] Banaras Hindu Univ, Inst Technol, Dept Elect Engn, Varanasi 221005, Uttar Pradesh, India
来源：
COMPUTERS & ELECTRICAL ENGINEERING | 2003年 / 29卷 / 03期
关键词：
radial basis function; neural networks; differential relay; power transformer;
D O I：
10.1016/S0045-7906(01)00033-7
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Function approximation has been found in many applications. The radial basis function network is one of the approaches which has shown a great promise in this sort of problems because of its faster learning capacity, The application of RBF neural network for differential relaying of power transformer is presented in this paper. Performance of this model is compared with feed-forward neural network (FFNN). The proposed method of power transformer protection is evaluated using simulation performed with EMTP package. The proposed model requires less training time and is more accurate in prediction as compared to FFNN. (C) 2002 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：421 / 434
页数：14
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