# Application of Artificial Neural Networks in Estimating Participation in Elections

arXiv: https://arxiv.org/abs/1309.2183 · HTML: https://mlsanity.com/paper/1309.2183/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Sep 2013.

## Built on by (most cited first, 1 of 1)

- [OpTorch: Optimized deep learning architectures for resource limited environments](https://mlsanity.com/paper/2105.00619/) (2021)

## Abstract (arXiv)

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.