Reports on Fuzzy Information and Engineering Findings from Faculty of Science and Technology Provide New Insights (Genetic Algorithm Approaches for Parameter Estimation and Global Stability in Fuzzy Epidemic Modeling).

A recent study published in the journal Fuzzy Information and Engineering explores the use of genetic algorithms and fuzzy set theory in epidemic modeling. The research, conducted by the Faculty of Science and Technology at Oxus University in Tashkent, Uzbekistan, emphasizes the need for sophisticated modeling techniques to better understand and predict dynamic scenarios in epidemiology. The study proposes a novel approach that integrates continued fraction theory and a genetic algorithm to fit real-world epidemic data, providing insights crucial for public health planning and control measures. By addressing unexplored facets and bridging gaps in previous research, the study contributes to a more comprehensive understanding of epidemic dynamics and offers a foundation for effective public health strategies in the face of infectious diseases. [Extracted from the article]