Year: 2025
Type: conference-paper
Abstract: Literature [2] proposed a sparrow search algorithm (SSA) based on an adaptive hybrid strategy, which uses chaotic mapping in the population initialization stage to enable the algorithm to explore a broader solution space. Literature [5] proposed an improved northern goshawk optimization algorithm, which uses adaptive t-distribution mutation to perturb and update the optimal solution, thereby enhancing the algorithm's global optimization ability. It has been verified[1] that the improved algorithm is significantly better than the PSO algorithm in terms of avoiding premature convergence to local optimum, better than the WOA algorithm[3] in terms of local exploitation ability, and significantly better than the APO algorithm[4] in terms of balancing global and local search.
Authors: Yutian Su, Wendang Jiang
Institution: Jiangsu University of Science and Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4414128443