IIARD International Institute of Academic Research and Development

INTERNATIONAL JOURNAL OF APPLIED SCIENCES AND MATHEMATICAL THEORY (IJASMT )

E- ISSN 2489-009X
P- ISSN 2695-1908
VOL. 10 NO. 3 2024
DOI: 10.56201/ijasmt.v10.no3.2024.pg33.47

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Comparative Analysis of Some Population Growth Models and Blended Approaches Oke Samuel Abayomi,

Oke Samuel Abayomi, Oladimeji Lukman Abiola, Akinade Oludayo Olugbenga and Tijani Rokibat Adeola

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Abstract

Determining the population growth of a country is a crucial issue as very many of fundamental human rights such as education, shelter, foods, health care etc. solely depends on it. The population estimate of a country plays a vital role in making right decision by the government about the population developmental and other socioeconomic projects. However, over the years, there has been concern about the appreciation of government in the need for a reliable and accurate population projection but to no avail, this is because of the use of appropriate model. However some new models namely PAEGMLGM, PAGGMLGM and PAEGMGGM were proposed through blended approaches and a comparative analysis was carried out along side with exponential growth model, logistic growth model and geometric growth model in other to find an appropriate estimate that evaluate the accuracy of projection models from the actual projection of Nigeria population spanning from 2006 to 2050. Using the models, population projections for Nigeria were calculated and presented graphically. Based on the graphical representation, it was observed that out of the three proposed models, only two (PAEGMLGM and PAGGMLGM) were consistent due to their sustained closeness to the actual projection over an extended period of time. Hence, it can be recommended that the model which is obtained by the arithmetic average of both Exponential growth model and Logistic growth model (PAEGMLGM) and arithmetic average of Geometric growth model and Logistic growth model (PAGGMLGM) is the best model for Nigeria population projection.

keywords:

population projection; exponential growth model; logistics growth model; geometric

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