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基于模糊蚁群收敛控制的通信网络路径优化     被引量:1

Communication Network Based on Fuzzy Ant Colony Convergence Control Path Optimization

文献类型:期刊文献

中文题名:基于模糊蚁群收敛控制的通信网络路径优化

英文题名:Communication Network Based on Fuzzy Ant Colony Convergence Control Path Optimization

作者:朱敏 苏博

第一作者:朱敏

机构:[1]贵州大学农业生物工程研究院;[2]广西科技师范学院科技处;[3]贵州理工学院信息工程学院

第一机构:贵州大学农业生物工程研究院,贵州贵阳550003

年份:2016

卷号:0

期号:5

起止页码:272-276

中文期刊名:计算机仿真

外文期刊名:Computer Simulation

收录:CSTPCD;;北大核心:【北大核心2014】;CSCD:【CSCD_E2015_2016】;

基金:贵州省科技厅自然科技基金(qian J word[2012]2012)

语种:中文

中文关键词:模糊控制;蚁群优化;通信网络;路径

外文关键词:Fuzzy control; Ant colony optimization; Communication network; The path

摘要:对通信网络路径进行优化,在提高通信网络利用率方面具有重要意义。传统的通信网络路径进行优化时,采用蜂群信息素释放追踪方法,随着蜂群个体中的扰动的变化,确定通信路径,导致路径选取精度差,效率低的问题。为此提出基于模糊蚁群收敛控制的通信网络路径优化算法。构建蚁群算法数学模型,采用重采样测量方法在通信网络路径规划过程中获取信息素浓度差异特征,引入基本蚁群个体滤波算法进行邻域变化调整,在通信网络动态决策范围内,得到每个个体避障的目标函数,实现模糊蚁群收敛控制,优化通信网络路径。仿真结果表明,采用改进的法进行通信网络路径优化,具有较好的通信性能,收敛性较好,误差降低,应用价值较高。
Optimizing the communication network path is important in improving the communication network utilization.When optimizing the traditional communication network path in the method of tracing the colony pheromone released,and to ensure the communication path with the distured change of colony unit.resulting problems of the low accuracy of path selection and the efficiency.An optimization algorithm of communication network path which is based on similar ant convergence control is proposed.Establishing a mathematical model of ant colony algorithm,and to get the information of pheromone concentration difference in the communication network path planning by means of resample measure,introducing basic ant unit filtering algorithm to adjust the change of neighbourhood,in the dynamic decision range of communication network,to get the objective function which is avoided by everyone,to realize the similar ant convergence control and optimize the communication network path.Simulation experiment shows that optimizing the communication network path in the improved method has better communication performance,better astringency.lower error and higher application value.

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