Title of article
Neural network architecture selection: new Bayesian perspectives in predictive modelling: Application to a soil hydrology problem
Author/Authors
Vila، نويسنده , , Jean-Pierre and Wagner، نويسنده , , Vérène and Neveu، نويسنده , , Pascal and Voltz، نويسنده , , Marc and Lagacherie، نويسنده , , Philippe، نويسنده ,
Pages
12
From page
119
To page
130
Abstract
The aim of this paper is to present to the community of ecologists concerned with predictive modelling by feedforward neural network, a new statistical approach to select the best neural network architecture (number of layers, number of neurons per layer and connectivity) in a set of several candidate networks. The interest of this approach is demonstrated on a soil hydrology problem.
Keywords
NEURAL NETWORKS , Non-linear regression , Bayesian model selection , Soil sciences , ecological modelling
Journal title
Astroparticle Physics
Record number
2079623
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