Predicting the Timing of Water Main Failure Using Artificial Neural Networks-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Predicting the Timing of Water Main Failure Using Artificial Neural Networks

Published:2014-04 Issue:4 Volume:140 Page:425-434
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Harvey Richard¹,McBean Edward A.²,Gharabaghi Bahram³

Affiliation:

1. Ph.D. Candidate, School of Engineering, Univ. of Guelph, Guelph, ON, Canada N1G 2W1 (corresponding author).

2. Canada Research Chair of Water Supply Security and Professor, School of Engineering, Univ. of Guelph, Guelph, ON, Canada N1G 2W1.

3. Associate Professor, School of Engineering, Univ. of Guelph, Guelph, ON, Canada N1G 2W1.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29WR.1943-5452.0000354

Reference50 articles.

1. Predicting water pipe breaks using neural network;Ahn J. C.;J. Water Sci. Technol. Water Supply,2005

2. Infrastructure Management: Integrated AHP/ANN Model to Evaluate Municipal Water Mains’ Performance

3. A new methodology for modelling break failure patterns in deteriorating water distribution systems: Theory

4. A new methodology for modelling break failure patterns in deteriorating water distribution systems: Applications

5. Asnaashari A. McBean E. Gharabaghi B. and Tutt A. (2013). “Forecasting watermain failure using artificial neural network modeling.” Can. Water Res. J. 38(1) 24–33.0701-178410.1080/07011784.2013.774153

Cited by 61 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Framework for Predicting Water Main Breaks in the Face of Climate Change;World Environmental and Water Resources Congress 2024;2024-05-16

2. Fractal Characteristics of Water Outflows on the Soil Surface after a Pipe Failure;Water;2024-04-25

3. Explainable ensemble models for predicting wall thickness loss of water pipes;Ain Shams Engineering Journal;2024-04

4. Evaluating the generalizability and transferability of water distribution deterioration models;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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3