Bayesian Approach for Real-Time Probabilistic Contamination Source Identification-Reference-Cited by-同舟云学术

Bayesian Approach for Real-Time Probabilistic Contamination Source Identification

Published:2014-08 Issue:8 Volume:140 Page:04014019
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Yang Xueyao¹,Boccelli Dominic L.²

Affiliation:

1. Environmental Engineering Program, Dept. of Biomedical, Chemical and Environmental Engineering, Univ. of Cincinnati, 701 Engineering Research Center, P.O. Box 210012, Cincinnati, OH 45221-0012.

2. Associate Professor, Environmental Engineering Program, Dept. of Biomedical, Chemical and Environmental Engineering, Univ. of Cincinnati, 701 Engineering Research Center, P.O. Box 210012, Cincinnati, OH 45221-0012 (corresponding author).

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.1943-5452.0000381

Reference37 articles.

1. Allgeier S. C. Pulz J. and Murray R. (2006). “Conceptual design of a contamination warning system.” Proc. Water Security Congress AWWA Washington DC.

2. Berry J. et al. (2010). “User’s manual: TEVA-SPOT toolkit 2.4.” EPA 600/R-08/041B National Homeland Security Research Center U.S. EPA Washington DC.

3. Sensor Placement in Municipal Water Networks with Temporal Integer Programming Models

4. Boccelli D. L. et al. (2004). “Tracer tests for network model calibration.” Proc. World Water and Environmental Resources Congress G. Sehlke D. F. Hayes and D. K. Stevens eds. ASCE Reston VA.

5. Real-time detection of intentional chemical contamination in the distribution system;Byer D.;J. Am. Water Works Assoc.,2005

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