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- W2262491224 abstract "At work, we propose the use of artificial neural networks for forecasting electricity consumption. Key influencers in the consumption of electricity in the country's public sector factors were studied. Major influential variables are determined in the consumption of electricity. Forecasting methods consuming more electricity used artificial neural networks being chosen as the most accurate were analysed. Was created, simulated and validated a neural network for forecasting electricity consumption yielding an error of approximation of 5.87%, due to the existence of few training data. The validity of the proposed method comparing the predicted results was found, resulting in a difference of 31.77 MWh. This value could be obtained to determine the technical potential and economic benefits." @default.
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- W2262491224 date "2014-01-01" @default.
- W2262491224 modified "2023-09-24" @default.
- W2262491224 title "PRONOSTICO DE CONSUMO DE ENERGÍA ELÉCTRICA USANDO REDES NEURONALES ARTIFICIALES." @default.
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