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

Hong Xiang Wang; Wen Xian Guo

doi:10.4028/www.scientific.net/AMR.267.605

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 267Upgrading Water Distribution System Based on...

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

Abstract:

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.

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Periodical:

Advanced Materials Research (Volume 267)

Pages:

605-608

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.267.605

Citation:

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Online since:

June 2011

Authors:

Hong Xiang Wang, Wen Xian Guo

Keywords:

Calibration, Genetic Algorithm (GA), RBF Neural Network, Water Distribution System

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