摘要
在分析捕鱼算法不足的基础上,提出了一种求解绝对值方程的改进捕鱼算法。该算法通过使用新的撒网方法来降低计算机内存消耗并减少计算量,从而提高算法性能。数值实验结果表明,在求解高维绝对值方程时,与捕鱼算法相比,改进捕鱼算法具有内存占用低、运行速度快等优点;与粒子群等群智能算法相比,改进捕鱼算法在求解精度等各项指标上均优于其他对比算法。
Based on the analysis of the shortcomings of fishing algorithm, an improved fishing algorithm for solving absolute value equation is proposed. The algorithm uses a new method to reduce the computer memory consumption and reduce the amount of calculations, so as to improve the performance of the algorithm. The numerical results show that the improved fishing algorithm has the advantages of low memory consumption and fast running speed compared with the fishing algorithm when solving the high-dimensional absolute value equations;Compared with particle swarm optimization and other swarm intelligence algorithms, the improved fishing algorithm is superior to other comparison algorithms in solving accuracy and other indicators.
作者
陈建荣
陈建华
Chen Jianrong;Chen Jianhua(School of Public Health and Management,Youjiang Medical University for Nationalities,Baise 533000;You Jiang District Medical Security Service Center,Baise 533000)
出处
《现代计算机》
2021年第32期27-32,共6页
Modern Computer
基金
2019年度广西高等教育本科教学改革工程项目(2019JGB305)
2020年右江民族医学院校级科研课题(yy2020gcky037)
2018年右江民族医学院校级科研课题(yy2018ky026)。
关键词
群智能算法
捕鱼算法
绝对值方程
改进算法
Swarm intelligence algorithm
fishing algorithm
absolute value equations
improved algorithm
