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
Link To Document :
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