Hourly and Daily Urban Water Demand Predictions Using a Long Short-Term Memory Based Model-Reference-Cited by-同舟云学术

Hourly and Daily Urban Water Demand Predictions Using a Long Short-Term Memory Based Model

Published:2020-09 Issue:9 Volume:146 Page:05020017
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Mu Li¹,Zheng Feifei²^ORCID,Tao Ruoling³,Zhang Qingzhou⁴,Kapelan Zoran⁵

Affiliation:

1. Deputy Chief Engineer, Hefei Water Supply Group Co. Ltd., No. 70, Tunxi Rd., Hefei, Anhui Province 230011, China.

2. Professor, College of Civil Engineering and Architecture, Zhejiang Univ., 866 Yuhangtang Rd., Hangzhou 310058, China (corresponding author). ORCID: .

3. Master Student, College of Civil Engineering and Architecture, Zhejiang Univ., Hangzhou 310058, China.

4. Postdoctoral Fellow, College of Civil Engineering and Architecture, Zhejiang Univ., 866 Yuhangtang Rd., Hangzhou 310058, China.

5. Professor, Faculty of Civil Engineering and Geosciences, Dept. of Water Management, Stevinweg 1, Delft Univ. of Technology, 2628 CN Delft, Netherlands.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29WR.1943-5452.0001276

Reference41 articles.

1. Estimation of residential water demand: a state-of-the-art review

2. Dynamic Forecast of Daily Urban Water Consumption Using a Variable-Structure Support Vector Regression Model

3. Box G. E. P. and G. M. Jenkins. 1976. Time series analysis: Forecasting and control. Hoboken NJ: Wiley.

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