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...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
المؤلفون الرئيسيون: Sun, Yu; Mutalib, Sofianita; Tian, Liwei
التنسيق: مقال
اللغة:English
منشور في: SCIENCE & INFORMATION SAI ORGANIZATION LTD 2025
الموضوعات:
الوصول للمادة أونلاين:https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001441772100001

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