Free Access
| Issue |
E.J.E.S.S.
Volume 14, Number 1, 2000
Neural Models in Economy and Management Science
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|
|---|---|---|
| Page(s) | 69 - 79 | |
| DOI | https://doi.org/10.1051/ejess:2000109 | |
DOI: 10.1051/ejess:2000109
European Journal of Economic and Social Systems 14 N
1 (2000) 69-79
Relative performance of the statistical learning network: An application of the price-quality relationship in the automobile
Pierre Desmet
Professor at University Paris IX-Dauphine and Essec;
E-mail: Pierre.Desmet@Dauphine.Fr
Abstract:
The design and topology of a neural network is still an important
and difficult task. To solve the problems of topology posed by the introduction
of connexionism, new approaches are proposed, and especially a combination of
induction rules with a statistical estimation of the neuron coefficients for
each layer. This research aims to compare an algorithm of this SLN approach with
traditional methods (regression and classical BP neural networks) using the
gradient method. Methods are put into application to determine the price-quality
relationship of a complex product, the automobile, according to the hedonic
price model. This application of the price-quality relationship to the English
automobile market leads to the conclusion that the claimed superiority of this
approach is unsubstantiated since, compared to the BP neural networks and even
linear regression, the performance of the GMDH method is inferior.
Keywords: Connexionism, neural networks, hedonic prices,
statistical
learning networks
Copyright EDP Sciences 2000