Pesquisa Operacional | |
ARTIFICIAL NEURAL NETWORK AND WAVELET DECOMPOSITION IN THE FORECAST OF GLOBAL HORIZONTAL SOLAR RADIATION | |
Luiz Albino Teixeira Júnior1  Rafael Morais De Souza1  Moisés Lima De Menezes1  Keila Mara Cassiano1  José Francisco Moreira Pessanha1  Reinaldo Castro Souza1  | |
关键词: wavelet decomposition; artificial neural networks; forecasts; | |
DOI : 10.1590/0101-7438.2015.035.01.0073 | |
来源: SciELO | |
【 摘 要 】
This paper proposes a method (denoted by WD-ANN) that combines the Artificial Neural Networks (ANN) and the Wavelet Decomposition (WD) to generate short-term global horizontal solar radiation forecasting, which is an essential information for evaluating the electrical power generated from the conversion of solar energy into electrical energy. The WD-ANN method consists of two basic steps: firstly, it is performed the decomposition of level p of the time series of interest, generating p + 1 wavelet orthonormal components; secondly, the p + 1 wavelet orthonormal components (generated in the step 1) are inserted simultaneously into an ANN in order to generate short-term forecasting. The results showed that the proposed method (WD-ANN) improved substantially the performance over the (traditional) ANN method.
【 授权许可】
CC BY
All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License
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