Predicting Water Pipe Failures Using Deep Learning Algorithms-Reference-Cited by-同舟云学术

Predicting Water Pipe Failures Using Deep Learning Algorithms

Published:2023-09 Issue:3 Volume:29 Page:
ISSN:1076-0342
Container-title:Journal of Infrastructure Systems
language:en
Short-container-title:J. Infrastruct. Syst.

Author:

Liu Wei¹,Xie Zhiyin²,Song Zhaoyang³

Affiliation:

1. Associate Professor, Dept. of Structural Engineering, Tongji Univ., 1239 Siping Rd., Yangpu District, Shanghai 200092, China; Associate Professor, State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji Univ., 1239 Siping Rd., Yangpu District, Shanghai 200092, China.

2. Ph.D. Candidate, Dept. of Structural Engineering, Tongji Univ., 1239 Siping Rd., Yangpu District, Shanghai 200092, China.

3. Postdoctoral Fellow, Shanghai Chengtou Water Group Co., Ltd., 50 Jinling East Rd., Huangpu District, Shanghai 200021, China (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Subject

Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JITSE4.ISENG-2247

Reference54 articles.

1. Failure modeling of water distribution pipelines using meta-learning algorithms

2. Distribution-free ROC analysis using binary regression techniques

3. Handling class imbalance in customer churn prediction

4. SMOTE: Synthetic Minority Over-sampling Technique

5. Automated detection of sewer pipe defects in closed-circuit television images using deep learning techniques

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