Mounce S R, Day A J, Wood A S, Khan A, Widdop P D, Machell J
Department of Computing, Phoenix Building, University of Bradford, UK.
Water Sci Technol. 2002;45(4-5):237-46.
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.
本文描述了如何利用配水管网的水力和水质数据，为水行业提供更高效的漏损管理能力。所呈现的研究关注人工神经网络在处理后的配水系统漏损检测与定位问题上的应用。概述了基于人工神经网络（ANN）系统的架构。神经网络利用传感器产生的时间序列数据直接构建用于预测和分类泄漏的经验模型。使用来自约克郡水务公司基斯利配水系统实验场地的数据展示了结果。
