Flexible Neural Tree: Foundations and Applications

Abstract

Artificial neural networks (ANNs) have been successfully applied to a number of scientific and engineering fields in recent years, i.e., function approximation, system identification and control, image processing, time series prediction [58]. A neural network’s performance is highly dependent on its structure. The interaction allowed between the various nodes of the network is specified using the structure only. An artificial neural network structure is not unique for a given problem, and there may exist different ways to define a structure corresponding to the problem. Depending on the problem, it may be appropriate to have more than one hidden layer, feedforward or feedback connections, or in some cases, direct connections between input and output layer.