Papers
1
Total Citations
2
H-Index
1
About
Xi He is a researcher whose work bridges computational intelligence and health assessment, with a particular focus on adaptive optimization algorithms. His most cited paper, "Chaos Adaptive Particle Swarm for Physical Exercise Health Assessment" (2022), introduces a novel approach that enhances the standard Particle Swarm Optimization (PSO) algorithm by integrating chaotic dynamics and adaptive inertia weight mechanisms. This innovation optimizes Radial Basis Function Neural Network (RBFNN) models for evaluating physical exercise health, addressing key challenges in population diversification and convergence speed. While his citation count is currently modest, He’s contribution lies in refining swarm intelligence techniques for real-world health monitoring applications, offering a more robust and adaptive framework than conventional PSO methods. His work exemplifies the growing intersection of metaheuristic algorithms and personalized health assessment, providing a foundation for future research in adaptive fitness evaluation systems. As the field of computational health analytics expands, He’s algorithmic improvements hold potential for broader adoption in wearable technology and exercise science.
Research Focus
Key Achievements
Top Papers
- 1Chaos Adaptive Particle Swarm for Physical Exercise Health Assessment2 citations · 2022