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Method and system for predicting future population fine spatial distribution and computer readable storage medium

A technology of population distribution and spatial distribution, applied in the direction of prediction, calculation, kernel method, etc., can solve the problem that the future population cannot reflect the characteristics of the future population spatial distribution

Pending Publication Date: 2021-11-23
GUANGDONG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0006] The present invention provides a method, system and computer-readable storage medium for predicting the refined spatial distribution of the future population in order to overcome the disadvantages of the above-mentioned existing population prediction, which can only obtain the total population in the future and cannot reflect the spatial distribution characteristics of the future population.

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  • Method and system for predicting future population fine spatial distribution and computer readable storage medium
  • Method and system for predicting future population fine spatial distribution and computer readable storage medium
  • Method and system for predicting future population fine spatial distribution and computer readable storage medium

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Embodiment 1

[0044] Such as figure 1 As shown, the first aspect of the present invention provides a method for predicting the refined spatial distribution of future population, comprising the following steps:

[0045] S1: Determine the indicative factors of population distribution, and obtain the layer data of the indicative factors of population distribution in the area to be predicted;

[0046] It should be noted that, to construct the population spatialization model in the present invention, at first the indicative factors of population distribution must be selected. When selecting the indicative factors of population distribution, it is necessary to proceed from the main influencing factors of population distribution. Example POIs points (for example, supermarkets) can be selected. , schools and banks), roads, rivers and terrain elevations.

[0047]The layer data POIs layer, road layer, river layer and terrain elevation map of the population distribution indicative factor, in an embod...

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Abstract

The invention discloses a method and a system for predicting future population fine spatial distribution and a computer readable storage medium. According to the method, on one hand, the population scale is predicted, and on the other hand, a to-be-predicted area is subjected to research area division, a population spatialization model is constructed by combining a weight value of a population distribution indicative factor and a simulated land utilization type, and a predicted population scale is input into the population spatialization model to obtain future population fine spatial distribution, so that the problem of coupling of a population prediction method and the population spatialization model is solved, and the future population fine spatial distribution is predicted.

Description

technical field [0001] The present invention relates to the fields of spatio-temporal big data mining and spatio-temporal analysis, and more specifically, to a method, system and computer-readable storage medium for predicting the refined spatial distribution of future population. Background technique [0002] The current population forecasting methods are divided into two categories: mathematical statistical models and demographic method models. Commonly used mathematical statistical models include: Logistic model, GM (1,1) model and ARIMA model. This type of model only starts from the statistical characteristics of the total population, without fully considering the influence of demographic factors (ratio of male to female, total fertility rate and population of women of childbearing age, etc.). As a demographic method, the cohort factor method can make full use of the horizontal data in the demographic data (that is, the information of each age group) and effectively com...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/26G06F16/29G06N20/10
CPCG06Q10/04G06Q50/26G06F16/29G06N20/10
Inventor 龚镇杰何艳虎蔡宴朋杨志峰
Owner GUANGDONG UNIV OF TECH
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