Title of article
Best ANN Structures for Fault Location in Single- and Double-Circuit Transmission Lines
Author/Authors
J. Gracia، نويسنده , , A. J. Mazon، نويسنده , , I. Zamora، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2005
Pages
7
From page
2389
To page
2395
Abstract
The great development in computing power has allowed
the implementation of artificial neural networks (ANNs) in
the most diverse fields of technology. This paper shows how diverse
ANN structures can be applied to the processes of fault classification
and fault location in overhead two-terminal transmission lines,
with single and double circuit. The existence of a large group of
valid ANN structures guarantees the applicability of ANNs in the
fault classification and location processes. The selection of the best
ANN structures for each process has been carried out by means of
a software tool called SARENEUR.
Keywords
Artificial neural networks (ANNs) , fault classification , Fault location , LEARNING VECTOR QUANTIZATION , multilayer perceptron.
Journal title
IEEE TRANSACTIONS ON POWER DELIVERY
Serial Year
2005
Journal title
IEEE TRANSACTIONS ON POWER DELIVERY
Record number
400975
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