Comparative Analysis of Machine Learning and Survival Analysis Combinations for Water Main Failure Prediction-Reference-Cited by-同舟云学术

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Comparative Analysis of Machine Learning and Survival Analysis Combinations for Water Main Failure Prediction

Published:2023-12 Issue:4 Volume:29 Page:
ISSN:1076-0342
Container-title:Journal of Infrastructure Systems
language:en
Short-container-title:J. Infrastruct. Syst.

Author:

Vaags Eric¹^ORCID,Lence Barbara J.²,Kshirsagar Sudhir³^ORCID

Affiliation:

1. Graduate Research Assistant, Dept. of Civil Engineering, Univ. of British Columbia, Vancouver, BC, Canada V6T 1Z4 (corresponding author). ORCID: .

2. Professor, Dept. of Civil Engineering, Univ. of British Columbia, Vancouver, BC, Canada V6T 1Z4.

3. President, Global Quality Corp., 3071 Higgins Pl., Palo Alto, CA 94303. ORCID:

Publisher

American Society of Civil Engineers (ASCE)

Subject

Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JITSE4.ISENG-2176

Reference36 articles.

1. ASCE. 2021. 2021 report card for America’s infrastructure. Reston, VA: ASCE.

2. Forecasting watermain failure using artificial neural network modelling

3. An evaluation of machine learning techniques to predict the outcome of children treated for Hodgkin-Lymphoma on the AHOD0031 trial

4. Campanella K. C. Andreasen H. Diba J. Himmelberger J. Leighton J. Santini and K. Vause. 2016. “2015 establishing the level of progress in utility asset management survey results.” In Vol. 2016 of Proc. Water Environment Federation 462–490. Alexandria VA: Water Environment Federation.

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