Population prediction method for optimizing Leslie model based on genetic thought

Abstract

The invention relates to a population prediction method for optimizing a Leslie model based on a genetic thought, and the method comprises the steps: taking time and age as parameters, carrying out the discretization of the time at the same age interval, and building an initial model; introducing a genetic thought and combining with the initial model to calculate the proportion of the non-unisexual women and the proportion of the non-unisexual women of the male at a certain time period; calculating the wish fertility of the females at a certain time period or the total number of the next generation of females obtained after fertility, and further obtaining the total fertility rate; constructing a dynamic planning model in combination with the Leslie model; making reasonable population quantity, population structure, total growth rate and tending ratio prediction according to the dynamic planning model; on the basis of less data, and accurately predicting the future development trend ofthe population and the change trend of the population structure under a growth policy.

Description

technical field [0001] The invention belongs to the field of computer technology, and in particular relates to a population forecasting method based on the idea of ​​genetics to optimize the Leslie model. Background technique [0002] As an important factor affecting social and economic development, population has become one of the most concerned issues in the world. Therefore, studying the changes in the population structure of a country or region not only helps to explain various economic phenomena in the country or region, but also can effectively predict future economic changes. [0003] However, the current population forecasting model still has some technical difficulties to be solved. One of them is the impact of population policy on population development. Since our country is a country with a large population, in order to ensure an appropriate population size and an appropriate age structure, our country has proposed policies such as "family planning", "separate t...

AI Technical Summary

Problems solved by technology

But they are all inherently flawed and cannot be reasonably predicted under existing population policies

For example, they cannot simulate the iteration of the population under different policies, and can only make one-sided predictions through data

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