Project summary

The results of population forecasts form the basis for considerations about the future development of many other non-demographic characteristics of the population and entire real systems involving the people. These systems represent the main objects of our efforts to manage development processes at all levels of territorial division, from local and regional, through national and transnational, to the global level.

In recent years, the demand for national and sub-national population forecasts has been growing faster than the supply on the demography side. This imbalance has deepened with the implementation and monitoring of the 2030 Agenda adopted by UN member countries in 2015 and its Sustainable Development Goals (SDGs). It will continue to grow in connection with implementing programs covered by the UN Climate Action.

The need for operative, effective, and efficient forecasting requires the corresponding collection and processing of relevant information, dynamic performance of its forecast-oriented analysis, follow-up forecasting, user-friendly presentation of the obtained results, their continuous monitoring and the forecasts and forecasting process evaluation. Meeting these needs is only possible by revising and innovating current procedures and automating those activities within the population forecasting process that can be automated. At the same time, the demand for innovation does not only concern the technical but also the methodological side of population forecasting.

The purpose of the doctoral research project will be the examination and assessment of existing and development of innovative methods and algorithms that can significantly increase the degree of automation of population forecasting processes. The practical purpose of the work is to develop the architecture of the information system and its possible implementation based on the created algorithmic base.

To achieve the goal of the proposed research should deal with the following:

  • Analysis of the procedures, methods, and models applied in the process of population forecasting regardless of their possible automation,
  • Analysis of sources of demographic data in various countries and methods of their storage and development of methods for automating their processing and receipt,
  • Analysis of the software applications used for general data forecasting and assessment of their applicability in the field of demographic forecasting,
  • Proposal and approbation of the innovative approaches, methods and algorithms leading to the most reliable population forecast, and
  • Evaluation of the possibilities of future use of artificial intelligence in population forecasting in the context of the solutions proposed in the framework of this doctoral research.
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