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Math. Comput. Appl. 1996, 1(1), 159-164; doi:10.3390/mca1010159

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

Yildiz Technical University, Elec.- Electro. Fac., Electrical Eng. Dep., 80750 Beşiktaş, ISTANBUL, Turkey
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Published: 1 June 1996
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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.
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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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.

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Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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