A Novel Hybrid Model Based on CEEMDAN and Bayesian Optimized LSTM for Financial Trend Prediction
Financial time series prediction is inherently complex due to its nonlinear, nonstationary, and highly volatile nature. This study introduces a novel CEEMDAN-BO-LSTM model within a decomposition-optimization-prediction- integration framework to address these challenges. The Complete Ensemble Empiric...
| Published in: | INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS |
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| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
| Published: |
SCIENCE & INFORMATION SAI ORGANIZATION LTD
2025
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| Subjects: | |
| Online Access: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001441772100001 |