A Two-Stage Deep Fusion Integration Framework Based on Feature Fusion and Residual Correction for Gold Price Forecasting

A Two-Stage Deep Fusion Integration Framework Based on Feature Fusion and Residual Correction for Gold Price Forecasting

Given the far-reaching impact of the gold price on global financial markets, accurately predicting the gold price has become essential, with machine learning methods emerging as a prominent tool to tackle this challenge. Nonetheless, traditional single prediction models usually suffer from limited p...

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Bibliographic Details
Main Authors: Cihai Qiu, Yitian Zhang, Xunrui Qian, Chuhang Wu, Jiacheng Lou, Yang Chen, Yansong Xi, Weijie Zhang, Zhenxi Gong
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Feature fusion
integration model
price forecast
residual correction
Online Access:https://ieeexplore.ieee.org/document/10546955/
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https://ieeexplore.ieee.org/document/10546955/

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