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机构地区:[1]太原理工大学计算机软件学院,太原030024 [2]太原理工大学计算机科学技术学院,太原030024
出 处:《电脑开发与应用》2011年第5期26-28,共3页Computer Development & Applications
摘 要:针对动态克隆选择算法中检测器利用率低、全局性差的问题,提出将人工鱼群算法中具有全局性和快速收敛的追尾、聚群行为应用在动态克隆选择算法的检测器生成阶段,改进算法效率,同时解决由于随机生成检测器而带来的诸多问题。通过仿真实验,证明改进后的算法具备了人工鱼群算法的优势,弥补了自身系统前期收敛慢、检测器生成效率低的问题。As in the dynamic clone selection algorithm,the detector use factor is low,the overall importance is bad,this article proposed that the behavior of follows,gathers which has the overall importance and the rapid convergence in the artificial fish swarm algorithm applicant in the dynamic clone selection algorithm detector generation phase.Meanwhile,the efficiency of algorithm is improved,and many questions which stochastically the detector takes are solved.The simulation experiment indicated that the improved algorithm has the advantage of the artificial fish swarm algorithm and made up the question that earlier period to restrain slowly,the detector production efficiency low in its own system.
分 类 号:TP301.6[自动化与计算机技术—计算机系统结构]
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