Papers
3
Total Citations
101
H-Index
3
About
Shihong Yin is a leading researcher in computational intelligence and robotics, whose work bridges the gap between nature-inspired optimization algorithms and real-world engineering challenges. His primary research areas include metaheuristic optimization, swarm intelligence, and robotic kinematics, with a particular focus on enhancing the performance of bio-inspired algorithms for complex mechanical systems. Yin's most impactful contribution is the development of the DTSMA (Dominant Swarm with Adaptive T-distribution Mutation-based Slime Mould Algorithm), published in 2022, which has garnered 60 citations for its innovative approach to overcoming the slime mould algorithm's tendency toward local optima and poor exploration-exploitation balance. Building on this, his hybrid Equilibrium Optimizer Slime Mould Algorithm (EOSMA), with 36 citations, directly addresses the challenging inverse kinematics problem for 7-degree-of-freedom robotic manipulators, demonstrating practical engineering impact. Earlier in his career, Yin also contributed foundational work in robotics with an efficient algorithm for automatic generation of manipulator dynamic equations, implemented in the PC-based program ARDEG. With over 100 combined citations for his most influential works, Yin continues to shape the field of intelligent optimization, offering students and researchers powerful new tools for solving complex, high-dimensional problems in robotics and beyond.
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