scholarly journals Forecasting chlorine residuals in a water distribution system using a general regression neural network

2006 ◽  
Vol 44 (5-6) ◽  
pp. 469-484 ◽  
Author(s):  
Gavin J. Bowden ◽  
John B. Nixon ◽  
Graeme C. Dandy ◽  
Holger R. Maier ◽  
Mike Holmes
Keyword(s):  
Neural Network ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
General Regression Neural Network ◽  
General Regression ◽  
Chlorine Residuals

A Neural Network Approach for Modeling Water Distribution System

2017 ◽  
Author(s):  
Andrei S. Popa ◽  
Conor O'Toole ◽  
Juan Munoz ◽  
Steve Cassidy ◽  
Dallas Tubbs ◽  
...  
Keyword(s):  
Neural Network ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Network Approach ◽  
Neural Network Approach

Risk Analysis Model for Water Pipeline Leakage Based on FAHP and BPNN

2013 ◽  
Vol 441 ◽  
pp. 1093-1096
Author(s):  
Wen Zeng ◽  
Yong Ting Pan ◽  
Hong Mei Huang
Keyword(s):  
Neural Network ◽  
Risk Analysis ◽  
Bp Neural Network ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Economic Loss ◽  
Analysis Model ◽  
Initial State ◽  
Water Pipeline

Scientific analysis of the leakage of the water distribution system in city is very helpful to water supply network’s maintenance and renovation, and hence reduces negative social effect and economic loss. A leakage risk nalysis model for water distribution system was established based on fuzzy analytical hierarchy process (FAHP) and BP neural network (BPNN). This model introduces FAHP to reasonably ensure initial state of BP neural network, and uses weighted superposition to mend learning sample set of BP neural network. The water distribution system of a city in Zhejiang province P. R. China was selected to test the proposed risk analysis model, which verifise its feasibility and effectivity.

Upgrading Water Distribution System Based on GA-RBF Neural Network Model

2011 ◽  
Vol 267 ◽  
pp. 605-608 ◽  
Author(s):  
Hong Xiang Wang ◽  
Wen Xian Guo
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Radial Basis Function ◽  
Network Model ◽  
Basis Function ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Calibration Model ◽  
Radial Basis

Hydraulic network calibration model is to minimize the sum of the squares of the differences between the calibrated and initial pipe roughness estimates, under a set of constraints determined from a sensitivity matrix. The upgrading problem of water distribution system was put forward after the preferable network model was obtained. Radial Basis Function neural network (RBF) based on genetic algorithm (GA) was proposed to solve the model. Genetic algorithm was applied to optimize the parameters of the neural network, and overcome the over-fitting problem. Case study concludes that using Radial Basis Function neural network (RBF) based on genetic algorithm (GA) and good results were obtained.

scholarly journals Study on Integrated Simulation Model for the Chlorine Residuals Decrease in Water Distribution System

2012 ◽  
Vol 68 (7) ◽  
pp. III_165-III_173
Author(s):  
Takashi YAMAGUCHI ◽  
Toyono INAKAZU ◽  
Akira KOIZUMI ◽  
Yasuhiro ARAI ◽  
Satoshi TAMURA ◽  
...  
Keyword(s):  
Simulation Model ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Integrated Simulation ◽  
Chlorine Residuals
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