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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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Principais autores: Maulana Ahsan Fadillah, Yenni Angraini, Rahma Anisa
Format: Artigo
Sprog:Inglês
Udgivet: Department of Informatics, UIN Sunan Gunung Djati Bandung 2025-06-01
Serier:JOIN: Jurnal Online Informatika
Fag:
anomaly detection
lstm autoencoder
lstm
ocsvm
weather
Online adgang:https://join.if.uinsgd.ac.id/index.php/join/article/view/1571
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