Hourly Urban Water Demand Forecasting Using the Continuous Deep Belief Echo State Network
Effective and accurate water demand prediction is an important part of the optimal scheduling of a city water supply system. A novel deep architecture model called the continuous deep belief echo state network (CDBESN) is proposed in this study for the prediction of hourly urban water demand. The CD...
Main Authors: | Yuebing Xu, Jing Zhang, Zuqiang Long, Hongzhong Tang, Xiaogang Zhang |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-02-01
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Series: | Water |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-4441/11/2/351 |
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