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January 29, 2026Expert Systems with Applications

A framework for wind field forecasting from sparse observations via integrated tensor completion and prediction

Guojin Si Min Xie Fengqi Zhang Ting Xia Lifeng Xi

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Key Points

Wind field forecasting improves accuracy with sparse observations, reducing uncertainty in models.
Tensor completion techniques are essential for enhancing prediction quality, maximizing available data.
Integrated prediction methods yield more reliable forecasts over traditional models in wind field studies.
This framework could enable better planning for renewable energy generation, highlighting potential economic benefits.

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Implication

Observational analysis forecasts wind field using sparse data, suggesting improved accuracy in predictions.

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Cite This Study

Si et al. (2026) studied this question.

synapsesocial.com/papers/69a75d6fc6e9836116a277c9 https://doi.org/10.1016/j.eswa.2026.131401

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