期刊名称：International Journal of Computer Science & Information Technology (IJCSIT)
印刷版ISSN：0975-4660
电子版ISSN：0975-3826
出版年度：2013
卷号：5
期号：4
页码：93
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：This paper explores the application of artificial neural networks for online identification of a multimachinepower system. A recurrent neural network has been proposed as the identifier of the two area, four machinesystem which is a benchmark system for studying electromechanical oscillations in multimachine powersystems. This neural identifier is trained using the static Backpropagation algorithm. The emphasis of thepaper is on investigating the performance of the variants of the Backpropagation algorithm in training theneural identifier. The paper also compares the performances of the neural identifiers trained using variantsof the Backpropagation algorithm over a wide range of operating conditions. The simulation resultsestablish a satisfactory performance of the trained neural identifiers in identification of the test powersystem
