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

Abstract:

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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.

Info:

Periodical:

Edited by:

Xuejun Zhou

Pages:

199-202

DOI:

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

Citation:

A. J. Wang and C. L. Liu, "Improved PSO in Water Supply Systems Based on AHP-RS and RBF Neural Network", Applied Mechanics and Materials, Vols. 99-100, pp. 199-202, 2011

Online since:

September 2011

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Price:

$35.00

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