ArticleScientific reports2023
A non-singular fractional-order logistic growth model with multi-scaling effects to analyze and forecast population growth in Bangladesh.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- A behavioral game-theoretic model for vaccination with fractional-order imitation and aspiration dynamics.Scientific reports · 2025Article
- Demographic forecast modelling using SSA-XGBoost for smart population management based on multi-sources data.PloS one · 2025Article
- Modeling and analysis of dengue transmission in fuzzy-fractional framework: a hybrid residual power series approach.Scientific reports · 2024Article
- An innovative fractional-order evolutionary game theoretical study of personal protection, quarantine, and isolation policies for combating epidemic diseases.Scientific reports · 2024Article
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3 authors.
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Abstract
This paper is primarily concerned with data analysis employing the nonlinear least squares curve fitting method and the mathematical prediction of future population growth in Bangladesh. Available actual and adjusted census data (1974-2022) of the Bangladesh population were applied in the well-known autonomous logistic population growth model and found that all data sets of the logistic (exact), Atangana-Baleanu-Caputo (ABC) fractional-order derivative approach, and logistic multi-scaling approximation fit with good agreement. Again, the existence and uniqueness of the solution for fractional-order and Hyers-Ulam stability have been studied. Generally, the growth rate and maximum environmental support of the population of any country slowly fluctuate with time. Including an approximate closed-form solution in this analysis confers several advantages in assessing population models for single species. Prior studies predominantly employed constant growth rates and carrying capacity, neglecting the investigation of fractional-order methods. Thus, the current study fills a crucial gap in the literature by introducing a more formal approach to analyzing population dynamics. Therefore, we bank on the findings of this article to contribute to accurate population forecasting and planning, national development, and national progress.
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