基于遗传禁忌算法优化的模糊神经网络垂直切换算法

Fuzzy neural network based on genetic tabu algorithm to optimize vertical switching algorithm

针对异构网络切换问题,综合考虑遗传算法和禁忌算法的优点,结合神经网络及模糊理论,提出了基于遗传禁忌算法(GATS)优化的模糊神经网络垂直切换算法GATS-FNN。在切换过程中加入了预判决模块,通过筛选节点降低系统成本和算法复杂度;将网络信号强度、带宽、负载和用户终端移动速度进行了模糊处理,并采用GATS算法进行优化,调整隶属度函数的参数。仿真结果表明,该算法可以降低页面平均响应时间,为用户提供更好的服务。

Aimed at the problem of heterogeneous network handover,considered the advantages of genetic algorithm and tabu algorithm,combined the neural network and fuzzy theory,this paper proposed a fuzzy neural network based on genetic tabu algorithm（ GATS） to optimize the vertical switching algorithm. The algorithm it joined the preliminary judgment module in the process of switch,reduced the system cost and algorithm complexity through the screening of node. It put signal strength,bandwidth,load and the user terminal speed in fuzzy neural network processing module and used genetic tabu algorithm to optimize,adjusted the parameters of the membership function. Simulation experiments show that,this algorithm can reduce the average response time of pages,provide better service for the user.