Research on a Grey Prediction Model of Population Growth Based on a Logistic Approach

Mingyu Tong,Liu Chao,Zou Yan,Dorota Mozyrska

doi:10.1155/2020/2416840

Mingyu Tong, Liu Chao + Show 2 more

Open Access

https://doi.org/10.1155/2020/2416840

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Abstract

The classical population growth models include the Malthus population growth model and the logistic population growth model, each of which has its advantages and disadvantages. To address the disadvantages of the two models, this paper establishes a grey logistic population growth prediction model, based on the modeling mechanism of the grey prediction model and the characteristics of the logistic model, which uses the least-squares method to estimate the maximum population capacity. In accordance with the data characteristics of population growth, the weakening buffer operator is used to establish the weakening buffer operator grey logistic population growth prediction model, which improves its accuracy, thus improving the classic population prediction model. Four actual case datasets are used simultaneously, and the two classical grey prediction models are compared. The results of the six evaluation indicators show that the effects of the new model demonstrate obvious advantages. Finally, the new model is applied to the population forecast of Chongqing, China. The prediction results suggest that the population may reach a peak in 2020 and decline in the future. This finding is consistent with the logistic population growth model.

Highlights

A population that is too large or too small is not conducive to the overall development of a country
The population will grow geometrically, while the social resources on which humans depend for survival will grow arithmetically [1]. e Malthus population growth model is one of two classical population growth models; the population growth calculated by this model is infinite, but the balance between the population and social resources is disturbed after a period of unlimited population growth
Bloom and Freeman [3] studied the effects of rapid population growth on the labor supply and employment in developing countries

Summary

Introduction

A population that is too large or too small is not conducive to the overall development of a country. The logistic population growth model only needs three types of data, which can be used to obtain the two parameters of a binary nonlinear equation system. E empirical analysis of the logistic population grey model with a weakening buffer operator (LPGMWBO) shows that its simulation effect is better than that of the LGM. (2) e new model uses the modeling mechanism of the grey model, the least-squares method to estimate the maximum population capacity Nm, and the weakening buffer operator to optimize the accuracy of the new model. En, the LPGM is joined with a weakening buffer operator to establish the LPGMWBO, following which the nature of the models is studied.

Validation of the LPGMWBO

Applications

Malthus Population Growth Model

Findings

Logistic Population Growth Model