A FUSION MODEL FOR STOCK MARKET PREDICTION USING PROPHET AND LONG SHORT-TERM MEMORY NEURAL NETWORKS
Predicting the stock market can be difficult because of its inherent volatility and complexity. Machine learning approaches have demonstrated potential in identifying patterns and trends in financial data, enabling precise prediction-making in recent times. In this work, we combine the advantages of...
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| Principais autores: | , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
University of Kragujevac
2025-03-01
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| coleção: | Proceedings on Engineering Sciences |
| Assuntos: | |
| Acesso em linha: | https://pesjournal.net/journal/v7-n1/64.pdf |
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