Hydraulic Deterioration Models for Storm-Water Drainage Pipes: Ordered Probit versus Probabilistic Neural Network-Reference-Cited by-同舟云学术

Hydraulic Deterioration Models for Storm-Water Drainage Pipes: Ordered Probit versus Probabilistic Neural Network

Published:2010-03 Issue:2 Volume:24 Page:140-150
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Tran D. H.¹²³,Perera B. J. C.¹²³,Ng A. W. M.¹²³

Affiliation:

1. Postdoctoral Research Fellow, School of Engineering and Science, and Institute of Sustainability and Innovation, Victoria Univ., P.O. Box 14428 Melbourne, 8001 Victoria, Australia.

2. Professor, Faculty of Health, Engineering and Science, Victoria Univ., P.O. Box 14428, Melbourne, 8001 Victoria, Australia (corresponding author).

3. Senior Lecturer, School of Engineering and Science, Victoria Univ., P.O. Box 14428, Melbourne, 8001 Victoria, Australia.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000020

Reference51 articles.

1. Predicting Injury Severity Levels in Traffic Crashes: A Modeling Comparison

2. Condition Rating Model for Underground Infrastructure Sustainable Water Mains

3. Assessment of Infrastructure Inspection Needs Using Logistic Models

4. Predicting Cost Deviation in Reconstruction Projects: Artificial Neural Networks versus Regression

5. Estimating Transition Probabilities in Markov Chain-Based Deterioration Models for Management of Wastewater Systems

Cited by 22 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. Research note: Integrating big data to predict tree root blockages across sewer networks;Landscape and Urban Planning;2023-12

2. A multi-tier deterioration assessment models for sewer and stormwater pipelines in Hong Kong;Journal of Environmental Management;2023-11

3. A Deterioration Model for Sewer Pipes Using CCTV and Artificial Intelligence;Buildings;2023-04-03

4. A bilevel data-driven method for sewer deposit prediction under uncertainty;Water Research;2023-03

5. Laboratory and field experiment validations on the use of hydraulic transients for estimating buried water pipeline deterioration;Structural Health Monitoring;2022-05-26