title: A neural network approach to burst detection.
abstract: This paper describes how hydraulic and water quality data from a distribution network may be used to provide a more efficient leakage management capability for the water industry. The research presented concerns the application of artificial neural networks to the issue of detection and location of leakage in treated water distribution systems. An architecture for an Artificial Neural Network (ANN) based system is outlined. The neural network uses time series data produced by sensors to directly construct an empirical model for predication and classification of leaks. Results are presented using data from an experimental site in Yorkshire Water's Keighley distribution system.
authors.affiliation: Department of Computing, Phoenix Building, University of Bradford, UK.
authors.forename: S R
authors.initials: SR
authors.lastname: Mounce
authors.forename: A J
authors.initials: AJ
authors.lastname: Day
authors.forename: A S
authors.initials: AS
authors.lastname: Wood
authors.forename: A
authors.initials: A
authors.lastname: Khan
authors.forename: P D
authors.initials: PD
authors.lastname: Widdop
authors.forename: J
authors.initials: J
authors.lastname: Machell
mesh_terms: D000465:Algorithms; D004738:Engineering / Q000592:standards; D004739:England; D016571:Neural Networks, Computer; D055095:Optics and Photonics; D014881:Water Supply / Q000032:analysis* / Q000592:standards