A Review of Attention-Enhanced GRU Models with STL Decomposition for Food Loss Forecasting
Forecasting food loss with high accuracy is crucial for improving global food security, optimising supply chains, and supporting sustainability goals. However, conventional time series models and standard deep learning techniques, including recurrent neural networks (RNNs), often fall short in handl...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
The Science and Information (SAI) Organization Limited
2025
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/49868/3/A%20Review.pdf http://ir.unimas.my/id/eprint/49868/ https://thesai.org/Publications/ViewPaper?Volume=16&Issue=9&Code=IJACSA&SerialNo=38 |
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