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...
發表在: | INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS |
---|---|
Main Authors: | Sun, Yu; Mutalib, Sofianita; Tian, Liwei |
格式: | Article |
語言: | English |
出版: |
SCIENCE & INFORMATION SAI ORGANIZATION LTD
2025
|
主題: | |
在線閱讀: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001441772100001 |
相似書籍
-
Improved Whale Optimization Algorithm with LSTM for Stock Index Prediction
由: Sun, et al.
出版: (2025) -
Improved Whale Optimization Algorithm with LSTM for Stock Index Prediction
由: Sun Y.; Mutalib S.; Tian L.
出版: (2025) -
Behavioral Intrusion Prediction Model on Bayesian Network over Healthcare Infrastructure
由: 2-s2.0-85127342461
出版: (2022) -
Performance of Bayesian Model Averaging (BMA) for Short-Term Prediction of PM10 Concentration in the Peninsular Malaysia
由: Ramli N.; Abdul Hamid H.; Yahaya A.S.; Ul-Saufie A.Z.; Mohamed Noor N.; Abu Seman N.A.; Kamarudzaman A.N.; Deák G.
出版: (2023) -
Comparative Analysis of Hybrid 1D-CNN-LSTM and VGG16-1D-LSTM for Lung Lesion Classification
由: Jafery, et al.
出版: (2025)