Application of an improved LSTM model based on FECA and CEEMDAN VMD decomposition in water quality prediction

Abstract To address the limitations of existing water quality prediction models in handling non-stationary data and capturing multi-scale features, this study proposes a hybrid model integrating Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Variational Mode Decomposit...

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Autori principali:	Jie Long, Chong Lu, Yiming Lei, Zhong Yuan Chen, Yihan Wang
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Nature Portfolio 2025-04-01
Serie:	Scientific Reports
Soggetti:	Water quality monitoring CEEMDAN VMD LSTM FECA Hybrid model
Accesso online:	https://doi.org/10.1038/s41598-025-96941-4
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