Neural Network Based Prediction Models For Structural Deterioration of Urban Drainage Pipes

Full text for this resource is not available from the Research Repository.

Tran, D. H, Perera, B. J. C and Ng, A. W. M (2007) Neural Network Based Prediction Models For Structural Deterioration of Urban Drainage Pipes. In: MODSIM 2007 International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2007. Oxley, Les and Kulasiri, Don, eds. Modelling and Simulation Society of Australia and New Zealand, Christchurch, pp. 2264-2270.

Abstract

Structural deterioration of drainage pipes has been a major concern for asset managers in maintaining the required performance of the urban drainage systems. Structural deterioration is the reduction of physical integrity, which can be characterized through structural defects such as cracks and fractures that are identified through condition assessment. Due to limited budget and the massive number of pipes, condition assessment often is carried out on a fraction of the pipe network using closed circuit television (CCTV) inspection and a condition grading scheme. The condition assessment identifies the serviceability of pipes in a scale from one to three with one being the perfect, two being the fair and three being the poor condition.

Item type Book Section
URI https://vuir.vu.edu.au/id/eprint/25271
Official URL http://www.mssanz.org.au/MODSIM07/papers/42_s3/Neu...
ISBN 9780975840047
Subjects Historical > FOR Classification > 0905 Civil Engineering
Current > Division/Research > College of Science and Engineering
Keywords neural network, drainage pipes, deterioration model, structural condition
Citations in Scopus 7 - View on Scopus
Download/View statistics View download statistics for this item

Search Google Scholar

Repository staff login