基于新搜索策略的改进法医调查算法
Improved forensic-based investigation algorithm based on new search strategy
肖辉辉 1段艳明 1谭黔林1
作者信息
- 1. 河池学院大数据与计算机学院,广西河池 546300
- 折叠
摘要
为解决法医搜索算法的搜索方程存在振荡等问题,构建一种改进的法医调查算法.引入均值机制和莱维飞行策略对分析调查结果进行改进,提高算法的勘探能力;调查方向充分使用当前个体的有效信息,引入自适应动态调整缩放因子及最优个体引导机制,增强算法的探索活力;利用趋优避劣方法对算法的追捕行动进行改进,改善种群个体质量;追捕行动扩展采用单优学习策略解决振荡问题.求解11个标准函数和无线传感网络覆盖问题的结果显示,与对比算法比较,改进算法的优化能力具有显著优势.
Abstract
To solve the problems that the search equation of the forensic search algorithm has oscillation,etc.,an improved forensic-based investigation algorithm was constructed.The mean mechanism and Lévy flight strategy were introduced to modify the analysis results to improve the exploration ability of the algorithm.In the investigation direction part of the algorithm,the effective information of the current individual was fully used,and the adaptive dynamic adjustment scaling factor and the optimal individual guidance mechanism were introduced to enhance the exploration vitality of the algorithm.The pursuit action of the algorithm was improved using the method of optimizing and avoiding inferiority,to improve the quality of population individuals.To solve the oscillation phenomenon of pursuit operation expansion,a single-optimal learning strategy was adopted in this part.The results of solving 11 standard functions and wireless sensor network coverage problems show that compared with the com-parison algorithm,the optimization ability of the improved algorithm has significant advantages.
关键词
法医调查算法/无线传感网络/莱维飞行/优化能力/趋优避劣/缩放因子/单优学习Key words
forensic-based investigation algorithm/wireless sensor network/Lévy/optimization capabilities/optimizing and avoiding inferiority/scaling factor/single-optimal learning引用本文复制引用
基金项目
国家自然科学基金(61972184)
国家自然科学基金(61562032)
河池学院高层次人才科研启动基金(2019GCC012)
出版年
2024
NETL
NSTL
维普
万方数据