Combining recorded failures and expert opinion in the development of ANN pipe failure prediction models-Reference-Cited by-同舟云学术

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Combining recorded failures and expert opinion in the development of ANN pipe failure prediction models

Published:2020-07-14 Issue: Volume: Page:1-23
ISSN:2378-9689
Container-title:Sustainable and Resilient Infrastructure
language:en
Short-container-title:Sustainable and Resilient Infrastructure

Author:

Kerwin Sean¹^ORCID,Garcia de Soto Borja²³^ORCID,Adey Bryan¹,Sampatakaki Kleio⁴,Heller Hannes⁵

Affiliation:

1. Institute of Construction and Infrastructure Management, ETH Zurich, Zurich, Switzerland

2. Division of Engineering, New York University Abu Dhabi (NYUAD), Saadiyat Island, UAE

3. Tandon School of Engineering, New York University, Brooklyn, NY, USA

4. Gruner Wepf Zürich AG, Zurich, Switzerland

5. EBP Schweiz AG, Zurich, Switzerland

Publisher

Informa UK Limited

Subject

Safety, Risk, Reliability and Quality,Building and Construction,Geography, Planning and Development,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/23789689.2020.1787033

Reference91 articles.

1. Prediction of Water Pipe Asset Life Using Neural Networks

2. A road infrastructure asset management process: gains in efficiency and effectiveness

3. Predicting water pipe breaks using neural network

4. Maximum likelihood identification of Gaussian autoregressive moving average models

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1. Efficacy of Tree-Based Models for Pipe Failure Prediction and Condition Assessment: A Comprehensive Review;Journal of Water Resources Planning and Management;2024-07

2. Data augmentation using conditional generative adversarial network (cGAN): applications for sewer condition classification and testing using different machine learning techniques;Journal of Hydroinformatics;2024-06-13

3. Evaluation of ANN model for pipe status assessment in drinking water management;Water Supply;2024-05-01

4. Improving failure modeling for gas transmission pipelines: A survival analysis and machine learning integrated approach;Reliability Engineering & System Safety;2024-01

5. Models and explanatory variables in modelling failure for drinking water pipes to support asset management: a mixed literature review;Applied Water Science;2023-10-13

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