Enhancing Weather Monitoring for Agriculture with Deep Learning: Anomaly Detection in East Java Using LSTM Autoencoder and OCSVM
Agricultural productivity in East Java is under threat from unpredictable and harsh weather patterns, particularly rapid variations in sunlight length and rainfall intensity. These abnormalities can interrupt agricultural cycles, lower yields, and make farming communities more vulnerable to climati...
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| Autors principals: | , , |
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| Format: | Artigo |
| Idioma: | Inglês |
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Department of Informatics, UIN Sunan Gunung Djati Bandung
2025-06-01
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| Col·lecció: | JOIN: Jurnal Online Informatika |
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| Accés en línia: | https://join.if.uinsgd.ac.id/index.php/join/article/view/1571 |
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