Application of artificial neural networks in predicting voter turnout based on the analysis of demographic data

Piotr Michalak
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Abstract

Abstract The author presents the results of research on the use of artificial neural networks in predicting voter turnout. He describes the principles of operation of artificial neural networks, as well as detailed results of two machine learning methods used to predict voter turnout. The research resulted in creation of a functional model that allows for prediction of voter turnout results with a considerable degree of accuracy. The entire research process was carried out using the cartographic research method.
基于人口统计数据分析的人工神经网络在投票率预测中的应用
摘要本文介绍了利用人工神经网络预测选民投票率的研究成果。他描述了人工神经网络的运作原理,以及用于预测选民投票率的两种机器学习方法的详细结果。这项研究的结果是建立了一个功能模型,可以相当准确地预测投票率结果。整个研究过程采用地图学研究方法进行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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