Using some classical and neural networks methods for demography predicting

Muthanna Subhi Sulaiman, Osamah Basheer Shukur

Abstract


Studying the size of populations through demography predicting may analyze the relationships between these populations and the effects of economic, biological, and social processes. In this paper, the size and the growth of world population will be predicting. Poisson and logistic models will be used as classical statistical methods, while the intelligent method will be the recurrent neural networks (RNN) technique. The results reflect that the neural networks approach outperforms the classical methods in predicting the population size. As conclusion, the neural networks approach can give better predicting accuracy than the classical statistical methods.

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DOI: http://dx.doi.org/10.21533/pen.v8i1.1108

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Copyright (c) 2020 Muthanna Subhi Sulaiman, Osamah Basheer A. Shukur

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN: 2303-4521

Digital Object Identifier DOI: 10.21533/pen

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License