A Multi-Seasonal SS-MSTL-DR Approach With Efficient Training Using Deep Learning and LLaMA: A Case Study of 6-Element Air Quality Prediction in a Subtropical City

Large models and deep learning models for real-time services are trained from time to time to refresh the new features and achieve better accuracy. Multivariate time-series decomposition and recombination (MTS-DR) models effectively improve training efficiency. In this research, an MTS method that i...

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Principais autores:	Benedito Chi Man Tam, Su-Kit Tang, Alberto Cardoso
格式:	Artigo
語言:	Inglês
出版:	IEEE 2025-01-01
叢編:	IEEE Access
主題:	Air quality deep learning LLaMA MSTL multiseasonal scalable sub-models
在線閱讀:	https://ieeexplore.ieee.org/document/11184121/
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