Optimizing Health Pattern Recognition Particle Swarm Optimization Approach for Enhanced Neural Network Performance

Health pattern recognition is vital for advancing personalized healthcare interventions. This research introduces a synergistic approach, combining Fuzzy C-Means clustering with Particle Swarm Optimization (PSO), to optimize the hyperparameters of an Artificial Neural Network (ANN) and enhance health pattern recognition. Leveraging key features such as 'Smoker,' 'BMI,' and 'GenHlth,' Fuzzy C-Means reveals distinctive health clusters, providing nuanced insights into diverse health profiles within the dataset. Subsequently, the PSO algorithm systematically optimizes critical ANN hyperparameters, significantly decreasing the training loss to 0.004. This reduction underscores the effectiveness of the optimization process, indicating improved learning and predictive capabilities of the ANN. The proposed methodology not only refines health pattern recognition but also holds promise for personalized healthcare analytics. The identified clusters offer actionable insights for tailored interventions, addressing specific health profiles within the population. This research contributes to the evolving landscape of healthcare analytics by integrating advanced clustering and optimization techniques, paving the way for more effective and individualized healthcare strategies

Monitoring and Management of Natural Territorial Complexes

Abstract The paper describes the use of organization and graph theory for constructing model that management distributed nature and artificial beings. It 's proposed a virtual model of the organizat ion, focused on the imp lementation of monitoring, regard less of the size and remoteness of the objects of observation fro m the center. The algorith m of its construction, based on the representation of the model in the form of attributed tree, is described. The resulting virtual model can be considered as a basis for solving a nu mber of applications for mon itoring, including decision-making, knowledge acquisition, visualization of large structures, the construction of dynamic d igital maps, integration with other systems, etc