Battle of Water Demand Forecasting: An Optimized Deep Learning Model
Ensuring a steady supply of drinking water is crucial for communities, but predicting how much water will be needed is challenging because of uncertainties. As a part of Battle of Water Demand Forecasting (BWDF), this study delves into the application of Long Short-Term Memory (LSTM) networks for wa...
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| Main Authors: | Mohammadali Geranmehr, Alemtsehay G. Seyoum, Mostapha Kalami Heris |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-09-01
|
| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/69/1/56 |
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