The DOI matches its Crossref record; 271 of the 271 references it cites were found in a registry or an index.
A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization
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“To date, many ML methods have been used to forecast electricity supply and demand.”
From Tackling climate change with machine learning (2023) · cites this paper as [9]
Citations
Cites
An Algorithm for Least-Squares Estimation of Nonlinear Parameters
Marquardt, D. W. (1963) · Journal of the Society for Industrial and Applied Mathematics · doi:10.1137/0111030 · Cited by 30,728
A decision-theoretic generalization of on-line learning and an application to boosting
Freund, Y., & Schapire, R. E. (1997) · Journal of Computer and System Sciences · doi:10.1006/jcss.1997.1504 · Cited by 20,466
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
He, K., Zhang, X., Ren, S., & Sun, J. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.123 · Cited by 19,741
A fast learning algorithm for deep belief nets
Hinton, G. E., Osindero, S., & Teh, Y.-W. (2006) · Neural Computation · doi:10.1162/neco.2006.18.7.1527 · Cited by 16,336
Breiman, L. (1996) · Machine Learning · doi:10.1007/bf00058655 · Cited by 16,325
Extreme learning machine: Theory and applications
Huang, G.-B., Zhu, Q.-Y., & Siew, C.-K. (2006) · Neurocomputing · doi:10.1016/j.neucom.2005.12.126 · Cited by 13,285
Proceedings of IEEE International Conference on Computer Vision
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Elman, J. L. (1990) · Cognitive Science · doi:10.1207/s15516709cog1402_1 · Cited by 11,212
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Hertz, J., Krogh, A., Palmer, R., & Jensen, R. V. (1994) · The advanced book program · doi:10.1119/1.17491 · Cited by 8,477
Training feedforward networks with the Marquardt algorithm
Hagan, M., & Menhaj, M. B. (1994) · IEEE Transactions on Neural Networks · doi:10.1109/72.329697 · Cited by 7,778
Research works printed but not linked: 3
- Zervos, 2016, vol. 60
- Comello, 2018, The road ahead for solar PV power, vol. 92, 744
- Hansen, 1994, vol. 11, 625
Cited by
Sorted by citations
A review of green artificial intelligence: Towards a more sustainable future
Bolón-Canedo, V., Morán-Fernández, L., Cancela, B., & Alonso-Betanzos, A. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128096 · Cited by 486
Tackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336
Sustainable energies and machine learning: An organized review of recent applications and challenges
Ifaei, P., Nazari-Heris, M., Tayerani Charmchi, A. S., Asadi, S., & Yoo, C. (2023) · Energy · doi:10.1016/j.energy.2022.126432 · Cited by 79
Heo, S., Byun, J., Ifaei, P., Ko, J., Ha, B., Hwangbo, S., & Yoo, C. (2024) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2023.113933 · Cited by 31
Metadata
- Authors
- Ahmed, R., Sreeram, V., Mishra, Y., & Arif, M. D.
- Affiliations
- The University of Western Australia (AU)
- Queensland University of Technology (AU)
- International University of Business Agriculture and Technology (BD)
- Corresponding author
- Ahmed, R.
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2020-05
- Volume
- 124
- Pages
- 109792
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W3009377873
- Cited by
- 1,259
- References
- 271
- Citations by year
- 2026: 200 · 2025: 254 · 2024: 278 · 2023: 193 · 2022: 192 · 2021: 113 · 2020: 29
- FWCI
- 51.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Renewable and Sustainable Energy Reviews (publishedVersion)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Solar Radiation and Photovoltaics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Energy Load and Power Forecasting
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Photovoltaic System Optimization Techniques
- Keywords
- photovoltaic power forecasting, solar energy integration, solar irradiance, weather classification, cloud motion, data preprocessing, wavelet transform, generative adversarial networks, uncertainty quantification, hybrid neural network, ensemble forecasting, online sequential extreme learning machine, convolutional neural networks, genetic algorithm optimization, particle swarm optimization, forecast evaluation, short-term forecasting
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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