Zihao Guo
Papers
1
Total Citations
22
H-Index
1
About
Zihao Guo is an emerging researcher in computational intelligence and metaheuristic optimization, with a focus on enhancing swarm-based algorithms for global optimization problems. His most cited work, "A Sinh–Cosh-Enhanced DBO Algorithm Applied to Global Optimization Problems" (2024, 22 citations), addresses critical limitations in the Dung Beetle Optimization (DBO) algorithm—specifically its poor population initialization, slow search speed, and insufficient global exploration. By introducing a Sinh–Cosh transformation mechanism, Guo significantly improves the algorithm's convergence accuracy and search efficiency, offering a more robust tool for complex engineering and scientific optimization tasks. This contribution has quickly gained traction, demonstrating his ability to refine existing methods for real-world applicability. Guo’s research lies at the intersection of algorithm design and applied optimization, where he systematically identifies performance bottlenecks in popular metaheuristics and proposes mathematically grounded enhancements. His work is particularly relevant for students and researchers tackling high-dimensional, nonlinear optimization problems, as it provides both theoretical insight and practical improvements. With growing citations and a clear trajectory, Zihao Guo is establishing himself as a thoughtful innovator in the field of computational optimization.
Research Focus
Key Achievements
Top Papers
- 1A Sinh–Cosh-Enhanced DBO Algorithm Applied to Global Optimization Problems22 citations · 2024