A hybrid GA and SA algorithms for feature selection in recognition of hand-printed Farsi characters

Abstract

In this research a hybrid feature selection technique based on genetic and simulated annealing algorithms is proposed. this approach is evaluated by using Bayesian classifier on a dataset of hand-printed Farsi characters which includes 100 samples for each 33 hand-printed characters. The acquired results have been improved by correction of Simulated Annealing through considering two minimum and maximum thresholds.