LLMAir: Adaptive Reprogramming Large Language Model for Air Quality Prediction

Accurate and timely air quality prediction is crucial for cities and individuals to effectively take necessary precautions against potential air pollution. Existing studies typically rely on building prediction models based on large-scale monitoring data, often designed for specific tasks. Recently,...

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Bibliographic Details

Published in:	Proceedings - International Conference on Parallel and Distributed Systems pp. 423 - 430
Main Authors:	Fan, Jinxiao, Chu, Haolin, Liu, Liang, Ma, Huadong
Format:	Conference Proceeding
Language:	English
Published:	IEEE 10.10.2024
Subjects:	Air quality Air quality prediction Analytical models Atmospheric modeling Data models Large language models Monitoring Predictive models Regulators Semantics Spatiotemporal phenomena Urban data analysis
ISSN:	2690-5965
Online Access:	Get full text
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