Enhancing Time Series Product Demand Forecasting With Hybrid Attention-Based Deep Learning Models

Enhancing Time Series Product Demand Forecasting With Hybrid Attention-Based Deep Learning Models

Time series forecasting plays a crucial role in various industries, particularly in predicting product demand for effective supply chain management. This paper presents a novel approach to time series forecasting by leveraging advanced deep learning techniques, specifically focusing on hybrid models...

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Bibliographic Details
Main Authors: Xuguang Zhang, Pan Li, Xu Han, Yongbin Yang, Yiwen Cui
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Time series forecasting
deep learning
attention mechanisms
product demand prediction
Online Access:https://ieeexplore.ieee.org/document/10795122/
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https://ieeexplore.ieee.org/document/10795122/

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