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- W3091102213 abstract "The aim of this paper is to intoduce a biologically insipired methodology for energy price prediction multi-step ahead. The system combines a Genetic Algorithm (GA), Lindenmayer Systems, and Deep Neural Networks (DNNs). In the final section of the paper, we present some experiments to investigate the possibilities of the method, especially for scenarios in which DNNs should be evolved. The results for MLP networks show good ability to predict spikes and satisfactory accuracy according to error measures up to 9.8%. In 58.33% of the cases, ADEANN-Deep provides better results than other hybrid systems. Preliminary studies show that the LSTM network can predict the PLD value with a percentual error of up to 2.9%, which is lower than that obtained using multilayer perceptron networks and other methods." @default.
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- W3091102213 date "2020-07-01" @default.
- W3091102213 modified "2023-09-27" @default.
- W3091102213 title "Bio-Inspired System for Electricity Price Forecast in the Brazilian Market" @default.
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- W3091102213 doi "https://doi.org/10.1109/ijcnn48605.2020.9207679" @default.
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