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About

Zhiwei Ye is a researcher focused on computational intelligence, swarm optimization, and intelligent navigation systems. His work bridges bio-inspired algorithms and real-world applications, particularly in emergency evacuation modeling and autonomous robotics. In his highly cited 2022 paper, Ye developed an artificial fish swarm scheme using heterogeneous pheromones to simulate emergency evacuations in social networks, achieving 6 citations for its novel two-layer model that mimics prey, swarm, and follow behaviors. Expanding into path planning, his 2023 study on multi-strategy ensemble Harris hawks optimization (SDHHO) for mobile robot navigation garnered 4 citations, offering a robust solution for generating smooth, collision-free paths in complex environments. Ye also contributed to pedestrian detection through channel feature fusion and enhanced semantic segmentation, a 2023 work with 2 citations that improves safety in autonomous systems. His research demonstrates a consistent drive to optimize decision-making under constraints, with applications ranging from disaster response to robotics. By integrating swarm intelligence with practical engineering challenges, Ye’s work provides foundational algorithms for safer, more efficient autonomous systems, making him a notable figure in computational optimization and intelligent navigation.