A Two‐Stage Data‐Driven Spatiotemporal Analysis to Predict Failure Risk of Urban Sewer Systems Leveraging Machine Learning Algorithms-Reference-Cited by-同舟云学术

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A Two‐Stage Data‐Driven Spatiotemporal Analysis to Predict Failure Risk of Urban Sewer Systems Leveraging Machine Learning Algorithms

Published:2021-05-30 Issue:12 Volume:41 Page:2356-2391
ISSN:0272-4332
Container-title:Risk Analysis
language:en
Short-container-title:Risk Analysis

Author:

Fontecha John E.¹^ORCID,Agarwal Puneet¹^ORCID,Torres María N.²^ORCID,Mukherjee Sayanti¹^ORCID,Walteros Jose L.¹^ORCID,Rodríguez Juan P.³^ORCID

Affiliation:

1. Department of Industrial and Systems Engineering University at Buffalo Buffalo NY USA

2. Department of Structural, Civil and Environmental Engineering University at Buffalo Buffalo NY USA

3. Department of Civil and Environmental Engineering Universidad de los Andes Bogotá Colombia

Publisher

Wiley

Subject

Physiology (medical),Safety, Risk, Reliability and Quality

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/risa.13742

Reference97 articles.

1. Big Data and Predictive Analytics in Fire Risk Using Weather Data

2. Assessing climate sensitivity of peak electricity load for resilient power systems planning and operation: A study applied to the Texas region

3. Missing Data

4. ICLR Research, Paper Series;Allouche E. N.,2002

5. An investigation of the factors influencing sewer structural deterioration

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