Data-Driven Identification of Dynamic Quality Models in Drinking Water Networks-Reference-Cited by-同舟云学术

Data-Driven Identification of Dynamic Quality Models in Drinking Water Networks

Published:2023-04 Issue:4 Volume:149 Page:
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Wang Shen¹^ORCID,Chakrabarty Ankush²,Taha Ahmad F.³^ORCID

Affiliation:

1. Lecturer, School of Cyberspace Security, Beijing Univ. of Posts and Telecommunications, Beijing 100876, China. ORCID: .

2. Research Scientist, Dept. of Control and Dynamical Systems, Mitsubishi Electric Research Laboratories, Cambridge, MA 02139.

3. Associate Professor, Dept. of Civil and Environmental Engineering, Vanderbilt Univ., Nashville, TN 37235 (corresponding author). ORCID: .

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

https://ascelibrary.org/doi/pdf/10.1061/JWRMD5.WRENG-5431

Reference40 articles.

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2. Brunton S. L. J. L. Proctor and J. N. Kutz. 2013. “Compressive sampling and dynamic mode decomposition.” Preprint submitted December 18 2013. https://arxiv.org/abs/1312.5186.

3. Discovering governing equations from data by sparse identification of nonlinear dynamical systems

4. Compressed sensing and dynamic mode decomposition

5. Measuring and Modeling Chlorine Propagation in Water Distribution Systems

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