摘要
针对传统目标跟踪算法搜索范围小、跟踪精度低的缺点,提出一种基于遗传扰动机制的改进蝙蝠算法(GDBA),该算法引入了遗传竞争机制,根据优化的优劣情况调整遗传算法的交叉率和变异率,使得种群具有遗传性和变异性,同时扩大了搜索范围,提高了粒子多样性,改善了跟踪精度.
Aimed at the defect of small searching scope and low tracking accuracy of traditional target tracking algorithm,an improved bat algorithm(GDBA)is proposed based on genetic disturbance mechanism.In this algorithm,the genetic competitive mechanism is introduced to improve the bat algorithm,the crossover factor and the mutation rate in the genetic algorithm are adjusted according to the good-bad condition of optimization,so that the population will be made to have heritability and diversity and meantime,the searching range will be expanded and the tracking accuracy improved.
作者
杜先君
马金斗
DU Xian-jun;MA Jin-dou(College of Electrical and Information Engineering,Lanzhou Univ.of Tech.,Lanzhou 730050,China;Key Laboratory of Gansu Advanced Control for Industrial Process,Lanzhou Univ.of Tech.,Lanzhou 730050,China;National Demonstration Center for Experimental Electrical and Control Engineering Education,Lanzhou 730050,China)
出处
《兰州理工大学学报》
CAS
北大核心
2020年第1期106-110,共5页
Journal of Lanzhou University of Technology
关键词
竞争机制
跟踪精度
GDBA算法
粒子多样性
competition mechanism
tracking accuracy
GDBA algorithm
particle variety
作者简介
杜先君(1979-),男,浙江杭州人,博士,副教授.
