Stock price prediction using the Sand Cat Swarm Optimization and an improved deep Long Short Term Memory network
Stock price prediction remains a complex challenge in financial markets. This study introduces a novel Long Short-Term Memory (LSTM) model optimized by Sand Cat Swarm Optimization (SCSO) for stock price prediction. The research evaluates multiple algorithms including ANN, LSTM variants, Auto-ARIMA,...
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | Borsa Istanbul Review |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S221484502400156X |
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