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An integrated deep neural network framework for predicting the wake flow in the wind field

Research article (Energy, 2024) · cited 12× · AI/ML
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An integrated deep neural network framework for predicting the wake flow in the wind field

Summary

An integrated deep neural network framework for predicting the wake flow in the wind field is a scholarly article[1].

Key Facts

  • An integrated deep neural network framework for predicting the wake flow in the wind field's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). An integrated deep neural network framework for predicting the wake flow in the wind field. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-integrated-deep-neural-network-framework-for-predicting-the-wake-flow-in-the-wind-field
MLA “An integrated deep neural network framework for predicting the wake flow in the wind field.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-integrated-deep-neural-network-framework-for-predicting-the-wake-flow-in-the-wind-field.
BibTeX @misc{4ortxyz_an-integrated-deep-neural-network-framework-for-predicting-the-wake-flow-in-the-wind-field_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An integrated deep neural network framework for predicting the wake flow in the wind field}}, year = {2026}, url = {https://4ort.xyz/entity/an-integrated-deep-neural-network-framework-for-predicting-the-wake-flow-in-the-wind-field}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An integrated deep neural network framework for predicting the wake flow in the wind field — https://4ort.xyz/entity/an-integrated-deep-neural-network-framework-for-predicting-the-wake-flow-in-the-wind-field (retrieved 2026-05-24)

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