火力与指挥控制2024，Vol.49Issue(3)：65-72,8.DOI:10.3969/j.issn.1002-0640.2024.03.007
加入淘汰机制的改进麻雀搜索算法
Improved Sparrow Search Algorithm with Elimination Mechanism
摘要
Abstract
The traditional Sparrow Algorithm(SSA)has the advantages of high search accuracy and strong optimization ability,but such problems as premature convergence and easy to fall into the local optimal value in the iterative process also exist.To solve these problems,a Sparrow Search Algorithm(TESSA)with Tent chaotic mapping and last place elimination mechanism is proposed.The 2N segmented Tent chaotic mapping is used to initialize the population position.At the same time,the nonlinear last place elimination mechanism is introduced in the later stage of the algorithm iteration to improve its convergence speed and accuracy.After comparing the performance of TESSA with other four population intelligent algorithms in solving six benchmark functions,the convergence speed,optimization accuracy,standard error and other performance indicators of TESSA have obvious advantages.关键词
麻雀搜索算法/混沌映射/淘汰机制/函数优化Key words
sparrow search algorithm/chaotic mapping/elimination mechanism/function optimization分类
军事科技引用本文复制引用
周建新,侯宏瑶,郑日成..加入淘汰机制的改进麻雀搜索算法[J].火力与指挥控制,2024,49(3):65-72,8.基金项目
河北省自然科学基金资助项目(F2018209201) （F2018209201）
