Genetic Algorithm to Estimate Parameters of Indonesian Population Growth Model
Maya Rayungsari, Akhsanul In’am, Muhammad Aufin
Available Online 20 October 2020.
- https://doi.org/10.2991/assehr.k.201017.094How to use a DOI?
- genetic algorithm, parameter estimation, Indonesian population, growth model
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - https://doi.org/10.2991/assehr.k.201017.094 ID - Rayungsari2020 ER -