A novel prediction model of grounding resistance based on long short-term memory

This study aims to investigate the use of Long Short-Term Memory (LSTM) models for predicting temporal variations in grounding resistance using time series data. This analysis is the first to apply LSTM models to grounding resistance prediction, utilizing experimental data, including soil resistivit...

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Veröffentlicht in:	AIP advances 2025-01, Vol.15 (1)
Hauptverfasser:	Pu, Xinghai, Zhang, Jing, Wang, Fei, Xue, Shuai
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Error analysis Prediction models Predictions Rainfall Soil analysis Soil resistance Time dependence
Online-Zugang:	Volltext
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