2022
DOI: 10.1109/access.2022.3225406
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Supervised Machine Learning Techniques for the Prediction of the State of Charge of Batteries in Photovoltaic Systems in the Mining Sector

Abstract: One of the critical aspects in the mining sector is energy, being of great importance for the operation since if it were to stop, one of the consequences would be the loss of large amounts of money. The research objective is to predict the State of Charge of Batteries of equipment powered by photovoltaic solar panels in the mining sector based on automatic supervised learning techniques. A monitoring system records each energy variable programmed in the photovoltaic system, for which an analysis of the data ex… Show more

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“…If the evaluation results are inadequate, the model can be optimized by adjusting the model-parameters or using other techniques such as feature selection or feature engineering [31]. The constructed model can be used to predict TOC values in water treatment systems.…”
Section: F Machine Learning Evaluationmentioning
confidence: 99%
“…If the evaluation results are inadequate, the model can be optimized by adjusting the model-parameters or using other techniques such as feature selection or feature engineering [31]. The constructed model can be used to predict TOC values in water treatment systems.…”
Section: F Machine Learning Evaluationmentioning
confidence: 99%