A Combined Framework Based on Feature Selection and Multivariate Mixed-Frequency for Crude Oil Prices Point and Interval Forecasting-Reference-Cited by-同舟云学术

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A Combined Framework Based on Feature Selection and Multivariate Mixed-Frequency for Crude Oil Prices Point and Interval Forecasting

Published:2023 Issue: Volume:11 Page:144064-144083
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Long Jun¹^ORCID,Li Lue²^ORCID,Li Zejun¹^ORCID

Affiliation:

1. School of Mathematics and Information Science, Guangxi University, Nanning, China

2. School of Big Data and Artificial Intelligence, Guangxi University of Finance and Economics, Nanning, China

Funder

Guangxi Science and Technology Project

Guangxi Key Laboratory of Big Data in Finance and Economics

Guangxi First-Class Discipline Statistics Construction Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10364753.pdf?arnumber=10364753

Reference64 articles.

1. A sentiment-enhanced hybrid model for crude oil price forecasting

2. A dynamic clustering ensemble learning approach for crude oil price forecasting

3. Forecasting the real prices of crude oil: What is the role of parameter instability?

4. A multi-granularity heterogeneous combination approach to crude oil price forecasting

5. Forecasting crude oil price with multilingual search engine data

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