Downstream Water Level Prediction of Reservoir based on Convolutional Neural Network and Long Short-Term Memory Network-Reference-Cited by-同舟云学术

Downstream Water Level Prediction of Reservoir based on Convolutional Neural Network and Long Short-Term Memory Network

Published:2021-09 Issue:9 Volume:147 Page:04021060
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Zhang Zhendong¹,Qin Hui²^ORCID,Yao Liqiang³,Liu Yongqi¹,Jiang Zhiqiang⁴,Feng Zhongkai⁴,Ouyang Shuo⁵,Pei Shaoqian¹,Zhou Jianzhong⁶

Affiliation:

1. Ph.D. Student, School of Civil and Hydraulic Engineering, Huazhong Univ. of Science and Technology, Wuhan, Hubei 430074, China.

2. Professor, School of Civil and Hydraulic Engineering, Huazhong Univ. of Science and Technology, Wuhan, Hubei 430074, China (corresponding author). ORCID: .

3. Senior Engineer, Changjiang River Scientific Research Institute, Changjiang Water Resources Commission, Wuhan, Hubei 430010, China.

4. Associate Professor, School of Civil and Hydraulic Engineering, Huazhong Univ. of Science and Technology, Wuhan, Hubei 430074, China.

5. Senior Engineer, Bureau of Hydrology, Changjiang Water Resources Commission, Wuhan, Hubei 430010, China.

6. Professor, School of Civil and Hydraulic Engineering, Huazhong Univ. of Science and Technology, Wuhan, Hubei 430074, China.

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.1943-5452.0001432

Reference36 articles.

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4. Power Generation Scheduling for Integrated Large and Small Hydropower Plant Systems in Southwest China

5. A genetic algorithm for predicting the structures of interfaces in multicomponent systems

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