Paper Title:
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.

  Info
Periodical
Chapter
Chapter 2: Building Technology Science
Edited by
Xuejun Zhou
Pages
199-202
DOI
10.4028/www.scientific.net/AMM.99-100.199
Citation
A. J. Wang, 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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