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An Attempt to Replace System Dynamics with Discrete Rate Modeling in Demographic Simulations

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 12745)

Abstract

The usefulness of simulation in demographic research has been repeatedly confirmed in the literature. The most common simulation approach to model population trends is system dynamic (SD). Difficulties in a reliable mapping of population changes with SD approach have been however reported by some authors. Another simulation approach, i.e. discrete rate modeling (DRM), had not yet been used in population dynamics modelling, despite examples of this approach being used in the modelling of processes with similar internal dynamics. The purpose of our research is to verify if DRM can compete with the SD approach in terms of accuracy in simulating population changes and the complexity of the model. The theoretical part of the work describes the principles of the DRM approach and provides an overview of the applications of the DRM approach versus other simulation methods. The experimental part permits the conclusion that DRM approach does not match the SD in terms of comprehensive accuracy in mapping the behavior of cohorts of the complex populations. We have been however able to identify criteria for population segmentation that may lead to better results of DRM simulation against SD.

Keyword

  • Computer simulation
  • Population modeling
  • Decision support
  • Cross-sectional analysis
  • Operations research
  • Healthcare demand modeling

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Acknowledgments

This project was financed by a grant from the National Science Centre Poland, titled Simulation modeling of the demand for healthcare services. It was awarded based on Decision 2015/17/B/HS4/00306.

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Zabawa, J., Mielczarek, B. (2021). An Attempt to Replace System Dynamics with Discrete Rate Modeling in Demographic Simulations. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12745. Springer, Cham. https://doi.org/10.1007/978-3-030-77970-2_21

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  • DOI: https://doi.org/10.1007/978-3-030-77970-2_21

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