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- W2335200906 abstract "This paper explores the application of artificial neural networksfor online identification of a multimachine power system. A recurrent neural networkhas been proposedas the identifier of the two area, four machine system which is a benchmark system for studying electromechanical oscillations in multimachine power systems. This neural identifier is trained using the static Backpropagation algorithm. The emphasis of the paper is on investigating the performance of the variants of the Backpropagation algorithm in training the neural identifier. The paper also compares the performances of the neural identifiers trained using variants of the Backpropagation algorithm over a wide range of operating conditions . The simulation results establish a satisfactory performance of the trained neural identifiers in identification of the test power system." @default.
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- W2335200906 date "2013-08-31" @default.
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- W2335200906 title "Comparative Study of Backpropagation Algorithms in Neural Network Based Identification of Power System" @default.
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- W2335200906 doi "https://doi.org/10.5121/ijcsit.2013.5407" @default.
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