Neural network architecture selection: new Bayesian perspectives in predictive modelling: Application to a soil hydrology problem

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.