Application of Artificial Neural Networks in Estimating Participation in Elections

It is approved that artificial neural networks can be considerable effective in anticipating and analyzing flows in which traditional methods and statics aren’t able to solve. In this article, by using two-layer feedforward network with tan-sigmoid transmission function in input and output layers, we can anticipate participation rate of public in kohgiloye and Boyerahmad Province in future presidential election of Islamic Republic of Iran with 91% accuracy. The assessment standards of participation such as confusion matrix and ROC diagrams have been approved our claims.