Future of Information and Communication Conference (FICC) 2024
4-5 April 2024
Publication Links
IJACSA
Special Issues
Future of Information and Communication Conference (FICC)
Computing Conference
Intelligent Systems Conference (IntelliSys)
Future Technologies Conference (FTC)
International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 6, 2021.
Abstract: This paper proposes an ensemble model for wind speed forecasting using the recurrent neural network known as Gated Recurrent Unit (GRU) and data augmentation. For the experimentation, a single wind speed time series is used, from which four augmented time series are generated, which serve to train four GRU sub-models respectively, the results of these sub-models are averaged to generate the results of the proposal ensemble model (E-GRU). The results achieved by E-GRU are compared with those of each sub-model, showing that E-GRU outperforms the sub-models. Likewise, the proposal model (E-GRU) is compared with benchmark models without data augmentation such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), showing that E-GRU is much more precise, reaching a difference of around 15% with respect to the Relative Root mean Square Error (RRMSE) and 11% with respect to the Mean Absolute Percentage Error (MAPE).
Anibal Flores, Hugo Tito-Chura and Victor Yana-Mamani, “An Ensemble GRU Approach for Wind Speed Forecasting with Data Augmentation” International Journal of Advanced Computer Science and Applications(IJACSA), 12(6), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120666
@article{Flores2021,
title = {An Ensemble GRU Approach for Wind Speed Forecasting with Data Augmentation},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120666},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120666},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {6},
author = {Anibal Flores and Hugo Tito-Chura and Victor Yana-Mamani}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.