A novel interval estimation framework for wind power forecasting using multi-objective gradient descent optimization

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Chen, Yinsong ORCID: 0000-0002-3827-5304, Yu, Samson S, Lim, Chee Peng ORCID: 0000-0003-4191-9083 and Shi, Peng ORCID: 0000-0001-8218-586X (2024) A novel interval estimation framework for wind power forecasting using multi-objective gradient descent optimization. Sustainable Energy, Grids and Networks, 38. ISSN 2352-4677

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/48606
DOI 10.1016/j.segan.2024.101363
Official URL https://www.sciencedirect.com/science/article/pii/...
Subjects Current > FOR (2020) Classification > 4008 Electrical engineering
Current > FOR (2020) Classification > 4611 Machine learning
Current > Division/Research > Institute for Sustainable Industries and Liveable Cities
Keywords wind energy generation; wind power prediction; prediction interval; gradient descent; lower upper bound estimation; deep learning
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