中圖分類號： TP18
文獻標識碼： A
DOI： 10.20044/j.csdg.2097-1788.2022.02.012
引用格式： 吳超略，韋文山，郭羿，等. 基于t分布變異的改進麻雀搜索算法[J].網(wǎng)絡安全與數(shù)據(jù)治理，2022，41(2)：74-78.

Improved sparrow search algorithm based on t-distribution variation

Abstract： Aiming at the problems of slow convergence speed and difficult to jump out of local optimization of sparrow search algorithm, an improved sparrow search algorithm based on t-distribution mutation is proposed. After updating the position of the follower, the adaptive t-distribution mutation is introduced to disturb the position of the follower, avoid falling into local optimization and enhance the performance of the algorithm. By comparing gray wolf optimizer, moth-flame optimization and original sparrow search algorithm, simulation experiments are carried out on six benchmark functions. The experimental results and Wilcoxon′s signed rank test results both show that the convergence accuracy and speed of the proposed improved sparrow search algorithm are better than other algorithms, which can improve the convergence speed of the algorithm and enhance the ability of the algorithm to jump out of local extremum.

Key words : sparrow search algorithm；intelligent optimization algorithm；Sin map；t-distribution