Machine Learning Techniques Applied to the Harmonic Analysis of Railway Power Supply

نویسندگان

چکیده

Harmonic generation in power system networks presents significant issues that arise utilities. This paper describes a machine learning technique was used to conduct research study on the harmonic analysis of railway stations. The an investigation time series whose values represented total distortion (THD) for electric current. based information collected at station. In electrified substation, measurements currents and voltages were made during certain interval time. From current values, THD calculated using fast Fourier transform (FFT) results train adaptive ANN—GMDH (artificial neural network–group method data handling) algorithm. Following training, prediction model created, performance which investigated this study. developed THD. studied its parameters. model’s evaluated regression coefficient (R), root-mean-square error (RMSE), mean absolute (MAE). very good, with RMSE (root-mean-square error) value less than 0.01 higher 0.99. Another conclusion from our also performed well terms training (calculation speed).

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ژورنال

عنوان ژورنال: Mathematics

سال: 2023

ISSN: ['2227-7390']

DOI: https://doi.org/10.3390/math11061381