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Urban population prediction based on multi-objective lioness optimization algorithm and system dynamics model.

Dong Li1, Yanyan Yu2, Bo Wang1

  • 1School of Economics and Management, Xi'an University of Posts and Telecommunications, Xi'an, 710061, China.

Scientific Reports
|July 22, 2023
PubMed
Summary
This summary is machine-generated.

Urban population prediction is crucial for development. A new model combining lioness optimization and system dynamics forecasts Xi'an's population, identifying employment and birth policies as key growth drivers.

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Area of Science:

  • Urban planning
  • Demography
  • Computational modeling

Background:

  • Population size is intrinsically linked to economic and social development.
  • Scientific population projections are essential for effective urban development strategies.

Purpose of the Study:

  • To develop and validate an urban population prediction model.
  • To forecast population trends in Xi'an from 2019 to 2050.
  • To analyze the impact of various policies on future population dynamics.

Main Methods:

  • A hybrid model integrating a multi-objective lioness optimization algorithm with system dynamics.
  • Optimization of critical system dynamics parameters to enhance model objectivity.
  • Simulation of five policy factors (birth, employment, science & technology, healthcare, education) across three scenarios.

Main Results:

  • The model accurately predicted Xi'an's population from 2019 to 2050.
  • Xi'an's population is projected to peak at 147,939,242 in 2040.
  • Employment and fertility policies demonstrated the most significant positive impact on population size, followed by education, science & technology, and health policies.

Conclusions:

  • Employment and birth policies are the most effective levers for population growth.
  • Coordinated implementation of all five analyzed policies offers the fastest route to population increase.
  • The developed model provides a robust tool for scientific urban population strategy formulation.