Identifying Sampling Interval for Event Detection in Water Distribution Networks-Reference-Cited by-同舟云学术

Identifying Sampling Interval for Event Detection in Water Distribution Networks

Published:2012-03 Issue:2 Volume:138 Page:187-191
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Mounce Stephen R.¹²³,Mounce Richard B.¹²³,Boxall Joby B.¹²³

Affiliation:

1. Pennine Water Group, Dept. of Civil and Structural Engineering, Univ. of Sheffield, Sheffield S1 3JD, UK (corresponding author).

2. Dept. of Architecture, Univ. of Cambridge, Cambridge CB2 1PX, UK.

3. Pennine Water Group, Dept. of Civil and Structural Engineering, Univ. of Sheffield, Sheffield S1 3JD, UK.

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.1943-5452.0000170

Reference14 articles.

1. Chang C. C. and Lin C. J. (2001). “LIBSVM: A library for support vector machines.” 〈http://www.csie.ntu.edu.tw/~cjlin/libsvm〉 (Nov. 2 2010).

2. Artificial neural network model for a low cost failure sensor: Performance assessment in pipeline distribution;Khan A.;Int. J. Math. Comput. Sci.,2005

3. Online modelling of water distribution systems: a UK case study

4. MATLAB Version 7.2.0.635 [Computer software]. Mathworks Inc. Natick MA.

5. Burst detection using hydraulic data from water distribution systems with artificial neural networks

Cited by 24 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. Mapping Pressure Surge Source in Urban Water Networks: Integrating Low‐ and High‐Frequency Pressure Data With an Illustrative Real Case Study;Water Resources Research;2024-08

2. Integrated dynamic multi-threshold pattern recognition with graph attention long short-term neural memory network for water distribution network losses prediction: An automated expert system;Engineering Applications of Artificial Intelligence;2024-01

3. Gradual Leak Detection in Water Distribution Networks Based on Multistep Forecasting Strategy;Journal of Water Resources Planning and Management;2023-08

4. Deep learning-based burst location with domain adaptation across different sensors in water distribution networks;Computers & Chemical Engineering;2023-08

5. Developing Leak Detection Strategies in Water Distribution Networks Using Machine Learning Techniques;Geospatial and Soft Computing Techniques;2023