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INTELLIGENT OPTIMAL CONTROL OF NONLINEAR DIABETIC POPULATION DYNAMICS SYSTEM USING A GENETIC ALGORITHM.
- Source :
- System Research & Information Technologies / Sistemnì Doslìdžennâ ta Ìnformacìjnì Tehnologìï; 2024, Issue 1, p134-148, 15p
- Publication Year :
- 2024
-
Abstract
- Diabetes is a chronic disease affecting millions of people worldwide. Several studies have been carried out to control the diabetes problem, involving both linear and non-linear models. However, the complexity of linear models makes it impossible to describe the diabetic population dynamic in depth. To capture more detail about this dynamic, non-linear terms were introduced into the mathematical models, resulting in more complicated models strongly consistent with reality (capable of re-producing observable data). The most commonly used methods for control estimation are Pantryagain’s maximum principle and Gumel’s numerical method. However, these methods lead to a costly strategy regarding material and human resources; in addition, diabetologists cannot use the formulas implemented by the proposed controls. In this paper, the authors propose a straightforward and well-performing strategy based on non-linear models and genetic algorithms (GA) that consists of three steps: 1) discretization of the considered non-linear model using classical numerical methods (trapezoidal rule and Euler–Cauchy algorithm); 2) estimation of the optimal control, in several points, based on GA with appropriate fitness function and suitable genetic operators (mutation, crossover, and selection); 3) construction of the optimal control using an interpolation model (splines). The results show that the use of the GA for non-linear models was successfully solved, resulting in a control approach that shows a significant decrease in the number of diabetes cases and diabetics with complications. Remarkably, this result is achieved using less than 70% of available resources. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 16816048
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- System Research & Information Technologies / Sistemnì Doslìdžennâ ta Ìnformacìjnì Tehnologìï
- Publication Type :
- Academic Journal
- Accession number :
- 177523164
- Full Text :
- https://doi.org/10.20535/SRIT.2308-8893.2024.1.10