Tuning the structure and parameters of a neural network using an orthogonal simulated annealing algorithm

Abstract

Listen

Translate article

In this paper, an orthogonal simulated annealing algorithm (OSA) is applied to get an optimal network structure and parameters of a feedforward neural network at the same time. An orthogonal experimental design which based on OSA could efficiently generate large good candidate solutions by using a few computing cost. High performance of OSA-based method can be shown to efficiently obtain more accurate solution in prediction of the sunspot numbers problem, compare with other exited methods.