Research on stock prediction based on CED-PSO-StockNet time series model

Abstract To tackle the challenge of low accuracy in stock prediction within high-noise environments, this paper innovatively introduces the CED-PSO-StockNet time series model. Initially, the model decomposes raw stock data using the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise...

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Autors principals:	Xinying Chen, Fengjiao Yang, Qianhan Sun, Weiguo Yi
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2024-11-01
Col·lecció:	Scientific Reports
Matèries:	Stock prediction CEEMDAN Encoder-decoder Attention mechanism PSO
Accés en línia:	https://doi.org/10.1038/s41598-024-78984-1
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