Seasonality and neural networks: a new approach

This paper is a response to difficulties reported in applying feedforward neural networks (NNs) to seasonal data. The solution we propose is a modified network model which is pruned and optimised by means of Differential Evolution methods. The problem for NNs in the case of seasonality lies in the so-called 'universal approximation' property, which underpins the use of MLP networks as a vehicle fo…