Application of Artificial Neural Networks in Estimating Participation in Elections
Neural and Evolutionary Computing
2013-09-10 v1 Computers and Society
Abstract
It is approved that artificial neural networks can be considerable effective in anticipating and analyzing flows in which traditional methods and statics are not 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.
Keywords
Cite
@article{arxiv.1309.2183,
title = {Application of Artificial Neural Networks in Estimating Participation in Elections},
author = {Seyyed Reza Khaze and Mohammad Masdari and Sohrab Hojjatkhah},
journal= {arXiv preprint arXiv:1309.2183},
year = {2013}
}