LLM-ROM: A Novel Framework for Efficient Spatiotemporal Prediction of Urban Pollutant Dispersion

Deep learning-based flow field prediction for microclimate pollutant dispersion represents an emerging and promising methodology, where effectively integrating meteorological, spatial, and temporal information remains a critical challenge. To address this, we propose a novel non-intrusive reduced-or...

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Egile Nagusiak:	Pin Wu, Zhiyi Qin, Yiguo Yang
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	MDPI AG 2026-03-01
Saila:	AI
Gaiak:	application of artificial intelligence time-series forecasting dilated convolutional autoencoder pre-trained large language models
Sarrera elektronikoa:	https://www.mdpi.com/2673-2688/7/3/104
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