A data-driven multi-model methodology with deep feature selection for short-term wind forecasting

Research article (Applied Energy, 2017) · cited 315× · AI/ML
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A data-driven multi-model methodology with deep feature selection for short-term wind forecasting

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A data-driven multi-model methodology with deep feature selection for short-term wind forecasting is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). A data-driven multi-model methodology with deep feature selection for short-term wind forecasting. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-data-driven-multi-model-methodology-with-deep-feature-selection-for-short-term-wind-forecasting
MLA “A data-driven multi-model methodology with deep feature selection for short-term wind forecasting.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-data-driven-multi-model-methodology-with-deep-feature-selection-for-short-term-wind-forecasting.
BibTeX @misc{4ortxyz_a-data-driven-multi-model-methodology-with-deep-feature-selection-for-short-term-wind-forecasting_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A data-driven multi-model methodology with deep feature selection for short-term wind forecasting}}, year = {2026}, url = {https://4ort.xyz/entity/a-data-driven-multi-model-methodology-with-deep-feature-selection-for-short-term-wind-forecasting}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A data-driven multi-model methodology with deep feature selection for short-term wind forecasting — https://4ort.xyz/entity/a-data-driven-multi-model-methodology-with-deep-feature-selection-for-short-term-wind-forecasting (retrieved 2026-05-24)

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