Denoising or distortion: Does decomposition-reconstruction modeling paradigm provide a reliable prediction for crude oil price time series?-Reference-Cited by-同舟云学术

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Denoising or distortion: Does decomposition-reconstruction modeling paradigm provide a reliable prediction for crude oil price time series?

Published:2023-12 Issue: Volume:128 Page:107129
ISSN:0140-9883
Container-title:Energy Economics
language:en
Short-container-title:Energy Economics

Author:

Xu Kunliang,Niu Hongli

Funder

Humanities and Social Sciences Youth Foundation, Ministry of Education

Ministry of Education of the People's Republic of China

Publisher

Elsevier BV

Subject

General Energy,Economics and Econometrics

Reference47 articles.

1. A novel hybrid model for forecasting crude oil price based on time series decomposition;Abdollahi;Appl. Energy,2020

2. Modes decomposition method in fusion with robust random vector functional link network for crude oil price forecasting;Bisoi;Appl. Soft Comput.,2019

3. Crude oil price prediction: a comparison between AdaBoost-LSTM and AdaBoost-GRU for improving forecasting performance;Busari;Comput. Chem. Eng.,2021

4. Adaptive Bayesian support vector regression model for structural reliability analysis;Cheng;Reliab. Eng. Syst. Saf.,2021

5. Financial decision-making in markets and firms: a behavioral perspective;De Bondt;Handbooks Oper. Res. Manag. Sci.,1995

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Interval prediction of crude oil spot price volatility: An improved hybrid model integrating decomposition strategy, IESN and ARIMA;Expert Systems with Applications;2024-10

2. A novel integrated method for improving the forecasting accuracy of crude oil: ESMD-CFastICA-BiLSTM-Attention;Energy Economics;2024-10

3. Research on Agricultural Product Price Prediction Based on Improved PSO-GA;Applied Sciences;2024-08-06

4. A Combined Framework Based on Feature Selection and Multivariate Mixed-Frequency for Crude Oil Prices Point and Interval Forecasting;IEEE Access;2023

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