The Evaluation Model of the Hydropower Project Financing Risk 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. Firstly, the evaluation indicator system is constructed by AHP, then the evaluation indicators are discretized by RS neural network. And then, RBF neural network is used to evaluate the hydropower project financing risk. In order to grasp this evaluation model better, finally, the paper provides an example to demonstrate the application of this evaluation model.

Info:

Periodical:

Key Engineering Materials (Volumes 474-476)

Edited by:

Garry Zhu

Pages:

2243-2246

DOI:

10.4028/www.scientific.net/KEM.474-476.2243

Citation:

H. Zhao and L. M. Chen, "The Evaluation Model of the Hydropower Project Financing Risk Based on AHP-RS and RBF Neural Network", Key Engineering Materials, Vols. 474-476, pp. 2243-2246, 2011

Online since:

April 2011

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Price:

$35.00

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