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Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds
Published on: November 13, 2017
Engy El-Shafeiy1, Maazen Alsabaan2, Mohamed I Ibrahem3,4
1Department of Computer Science, Faculty of Computers and Artificial Intelligence, University of Sadat City, Sadat City 32897, Monufia, Egypt.
This study introduces Multivariate Multiple Convolutional Networks with Long Short-Term Memory (MCN-LSTM) for real-time water quality anomaly detection. The novel deep learning approach accurately identifies unexpected data, ensuring water safety and reliability.
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