• 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