Genetic Algorithm to Estimate Parameters of Indonesian Population Growth Model

DOI

10.2991/assehr.k.201017.094How to use a DOI?

Keywords

genetic algorithm, parameter estimation, Indonesian population, growth model

Abstract

In this study, the genetic algorithm is implemented to determine the most suitable growth models for Indonesian population data. The tested models are the simple models of Malthus and Verhulst. Parameters estimated in Malthus model include birth rate, death rate, and migration rate. Meanwhile, Parameters estimated in Verhulst model are intrinsic growth rate (birth rate minus death rate), carrying capacity, and migration rate. The model selection is based on the lowest average cost function value of each model. The value of the cost function is determined based on the distance between the population number in the model with the estimated parameters and the population number reported by worldbank.org. After determining the most appropriate model based on parameter estimation, simulation of the Indonesian population will be conducted for the upcoming years.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Maya Rayungsari
AU  - Akhsanul In’am
AU  - Muhammad Aufin
PY  - 2020
DA  - 2020/10/20
TI  - Genetic Algorithm to Estimate Parameters of Indonesian Population Growth Model
BT  - Proceedings of the International Conference on Community Development (ICCD 2020)
PB  - Atlantis Press
SP  - 426
EP  - 430
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.201017.094
DO  - 10.2991/assehr.k.201017.094
ID  - Rayungsari2020
ER  -