The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Innovative Second-Generation Wavelets Construction With Recurrent Neural Networks for Solar Radiation Forecasting
Open accessAbstract
Solar radiation prediction is an important challenge for the electrical engineer because it is used to estimate the power developed by commercial photovoltaic modules. This paper deals with the problem of solar radiation prediction based on observed meteorological data. A 2-day forecast is obtained by using novel wavelet recurrent neural networks (WRNNs). In fact, these WRNNS are used to exploit the correlation between solar radiation and timescale-related variations of wind speed, humidity, and temperature. The input to the selected WRNN is provided by timescale-related bands of wavelet coefficients obtained from meteorological time series. The experimental setup available at the University of Catania, Italy, provided this information. The novelty of this approach is that the proposed WRNN performs the prediction in the wavelet domain and, in addition, also performs the inverse wavelet transform, giving the predicted signal as output. The obtained simulation results show a very low root-mean-square error compared to the results of the solar radiation prediction approaches obtained by hybrid neural networks reported in the recent literature.
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Cites
The wavelet transform, time-frequency localization and signal analysis
Daubechies, I. (1990) · IEEE Transactions on Information Theory · doi:10.1109/18.57199 · Cited by 6,483
Recurrent neural networks and robust time series prediction
Connor, J. T., Martin, R. D., & Atlas, L. E. (1994) · IEEE Transactions on Neural Networks · doi:10.1109/72.279188 · Cited by 1,316
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Photovoltaic and solar power forecasting for smart grid energy management
Wan, C., Zhao, J., Song, Y., Xu, Z., Lin, J., & Hu, Z. (2015) · CSEE Journal of Power and Energy Systems · doi:10.17775/cseejpes.2015.00046 · Cited by 654
Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals
Quan, H., Srinivasan, D., & Khosravi, A. (2014) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2013.2276053 · Cited by 614
A Weather-Based Hybrid Method for 1-Day Ahead Hourly Forecasting of PV Power Output
Yang, H.-T., Huang, C.-M., Huang, Y.-C., & Pai, Y.-S. (2014) · IEEE Transactions on Sustainable Energy · doi:10.1109/tste.2014.2313600 · Cited by 469
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Li, J., Deng, D., Zhao, J., Cai, D., Hu, W., Zhang, M., & Huang, Q. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.3000184 · Cited by 269
Metadata
- Authors
- Capizzi, G., Napoli, C., & Bonanno, F.
- Venue
- IEEE Transactions on Neural Networks and Learning Systems
- Published
- 2012-11
- Volume
- 23
- Issue
- 11
- Pages
- 1805-1815
- ISSN
- 2162-237X (ISSN-L)
- 2162-2388
- OpenAlex
- W1987302169
- Cited by
- 188
- References
- 2
- FWCI
- 12.03
- Type
- journal article
- Language
- en
- Open access
- green
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- Capizzi, G., Napoli, C., & Bonanno, F. (2012). Innovative Second-Generation Wavelets Construction With Recurrent Neural Networks for Solar Radiation Forecasting. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2012.2216546
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