Paper Title:
Research on Freeway Investment Risk Assessment Model Based on Variable-Structure Neural Network
  Abstract

Neural network models have widely been applied in assessment and perdition of economic and social fields, including risk assessment. Thus, it becomes a subject for the theory of neural network to study how to improve accuracy in the premise of ensuring convergence rate of BP (Back Propagation) neural network. On the basis of recent studies and disadvantages of traditional BP neural network, in terms of structural optimization to improve accuracy, the paper presents a variable-structure neural network where it is re-linking randomly process from neurons of input layer to neurons of output layer and from neurons of hidden layer to neurons of output layer. Secondly, the variable structure neural network of re-linking random process is applied in freeway investment risk assessment. Results of a cast indicate that the proposed model is sufficiently reasonably.

  Info
Periodical
Advanced Materials Research (Volumes 361-363)
Chapter
Chapter 11: Environmental Protection and Economic Development
Edited by
Qunjie Xu, Honghua Ge and Junxi Zhang
Pages
1370-1377
DOI
10.4028/www.scientific.net/AMR.361-363.1370
Citation
Z. G. Wang, J. W. Li, "Research on Freeway Investment Risk Assessment Model Based on Variable-Structure Neural Network", Advanced Materials Research, Vols. 361-363, pp. 1370-1377, 2012
Online since
October 2011
Export
Price
$32.00
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