Consequence of Failure Modeling for Water Pipeline Infrastructure Using a Hierarchical Ensemble Fuzzy Inference System
Author:
Affiliation:
1. Ph.D. Student, Virginia Tech, ICTAS 2 Room 351, 1075 Life Science Circle, Blacksburg, VA 24061 (corresponding author). ORCID: .
2. Professor and Director, Virginia Tech, 117 Patton Hall, 750 Drillfield Dr., Blacksburg, VA 24061.
Publisher
American Society of Civil Engineers (ASCE)
Subject
Civil and Structural Engineering
Link
https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29IS.1943-555X.0000730
Reference43 articles.
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2. Blaha F. J. P. E. Gaewski P. R. McCary and G. T. Coates. 2014. “Revisiting the topic of liability for damage due to water main breaks or leaks.” In Proc. Pipelines 2014: From Underground to the Forefront of Innovation and Sustainability 1649–1662. Reston VA: ASCE. https://doi.org/10.1061/9780784413692.150.
3. Performance-based modelling of long-term deterioration to support rehabilitation and investment decisions in drinking water distribution systems
4. Bubtiena A. M. A. H. Elshafie and O. Jafaar. 2011. “Application of artificial neural networks in modeling water networks.” In Proc. 2011 IEEE 7th Int. Colloquium on Signal Processing and Its Applications 50–57. New York: IEEE. https://doi.org/10.1109/cspa.2011.5759841.
5. Chen C. G. Flintsch and I. Al-Qadi. 2004. “Fuzzy logic-based life-cycle costs analysis model for pavement and asset management.” Accessed November 1 2020. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.652.2084&rep=rep1&type=pdf.
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