Improved PSO in Water Supply Systems Based on AHP-RS and RBF Neural Network

Ao Jie Wang; Chao Lue Liu

doi:10.4028/www.scientific.net/AMM.99-100.199

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 99-100Improved PSO in Water Supply Systems Based on...

Improved PSO in Water Supply Systems Based on AHP-RS and RBF Neural Network

Abstract:

A evaluation model based on the integration of analytic hierarchy process(AHP)-rough set theory (RS) and radial basic function (RBF) neural network is put forward for grasping the hydropower project financing risk.The Particle Swarm Optimization (PSO) algorithm is implemented to optimize the node numbers of the hidden layers in the model. The study indicates that the AHP-RS and RBF neural network connecting with improved PSO method is an attractive alternative to the conventional regression analysis method in modeling water distribution systems.

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Periodical:

Applied Mechanics and Materials (Volumes 99-100)

Pages:

199-202

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.99-100.199

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Online since:

September 2011

Authors:

Ao Jie Wang, Chao Lue Liu

Keywords:

AHP-RS, Particle Swarm Optimization Algorithm (PSO), RBF Neural Network, Water Supply Systems

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