Leak Detection of Water Supply Networks Using Error-Domain Model Falsification-Reference-Cited by-同舟云学术

Leak Detection of Water Supply Networks Using Error-Domain Model Falsification

Published:2018-03 Issue:2 Volume:32 Page:04017077
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Moser Gaudenz¹,Paal Stephanie German²^ORCID,Smith Ian F. C.³

Affiliation:

1. Applied Computing and Mechanics Laboratory, School of Architecture, Civil and Environmental Engineering, Swiss Federal Institute of Technology, Lausanne 1015, Switzerland.

2. Zachry Dept. of Civil Engineering, College of Engineering, Texas A&M Univ., College Station, TX 77843 (corresponding author). ORCID: .

3. Professor, Applied Computing and Mechanics Laboratory, School of Architecture, Civil and Environmental Engineering, Swiss Federal Institute of Technology, Lausanne 1015, Switzerland.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000729

Reference41 articles.

1. Implicit state-estimation technique for water network monitoring

2. The detection of leaks in underground pipes;Babbitt H.;J. Am. Water Works Assoc.,1920

3. Barandouzi M. A. Mahinthakumar G. Brill E. D. and Ranjithan R. (2012). “Probabilistic mapping of water leakage characterizations using a Bayesian approach.” Proc. World Environmental and Water Resources Congress 2012 ASCE Reston VA 3248–3256.

4. A Basis for the Selection of a Response Surface Design

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