HIGHLIGHTS
SUMMARY
Despite the fact that there are numerous methods for state estimation, recent research has focused more on machine_learning methods for accurate measurement. A recurrent and feed-forward neural_network is used to solve the state estimation problem for given measurement data [21][22]. Using graphical neural_network (GNN), power flow parameters are estimated. Even though the predicted output value, did not compare GNN with other machine_learning techniques and not discussed errors. In this work estimated voltage magnitude and phasor angle using a neural_network compared with other ML techniques such as DT, SVM, E-boost, and Ebag . . .
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