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Article

An Artificial Neural Network Based Preestimation Fitler for Bad Data Defection, Identification and Elimination in State Estimation

by
Mehmet Uzunoğlu
*,
Celal Kocatepe
and
Recep Yumurtaca
Yildiz Technical University, Elec.- Electro. Fac., Electrical Eng. Dep., 80750 Beşiktaş, ISTANBUL, Turkey
*
Author to whom correspondence should be addressed.
Math. Comput. Appl. 1996, 1(1), 159-164; https://doi.org/10.3390/mca1010159
Published: 1 June 1996
Versions Notes

Abstract

State estimators are vitally important in energy control centers. The measurements that come from control system are generally analysed by a state estimator. Since there can always be bad measurements in the system, estimated value and the true value of the state estimator can be far from each other. In this paper, by using an artificial neural network (ANN), a bad data detection, identification and then elimination preestimation filter is outlined.

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MDPI and ACS Style

Uzunoğlu, M.; Kocatepe, C.; Yumurtaca, R. An Artificial Neural Network Based Preestimation Fitler for Bad Data Defection, Identification and Elimination in State Estimation. Math. Comput. Appl. 1996, 1, 159-164. https://doi.org/10.3390/mca1010159

AMA Style

Uzunoğlu M, Kocatepe C, Yumurtaca R. An Artificial Neural Network Based Preestimation Fitler for Bad Data Defection, Identification and Elimination in State Estimation. Mathematical and Computational Applications. 1996; 1(1):159-164. https://doi.org/10.3390/mca1010159

Chicago/Turabian Style

Uzunoğlu, Mehmet, Celal Kocatepe, and Recep Yumurtaca. 1996. "An Artificial Neural Network Based Preestimation Fitler for Bad Data Defection, Identification and Elimination in State Estimation" Mathematical and Computational Applications 1, no. 1: 159-164. https://doi.org/10.3390/mca1010159

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