摘要
民航通信系统属于复杂网络通信系统,系统的通信节点数目庞大,传统的复杂网络鲁棒性分析算法性测试结果存在失真。为此提出一种分层权重划分理论的鲁棒性分析模型,并应用到航空通信系统的鲁棒性检测中,塑造BP神经网络大型民航通信系统鲁棒性评价模型,对影响大型民航通信系统鲁棒性的各项指标进行打分,依据综合得分进行不同的加权,获取大型民航通信系统鲁棒性评价指标的分层权重样本测试数据,按照获取的大型民航通信系统信息以及信息的改变量,对自适应加权BP神经网络权向量进行修正,建立大型民航通信系统中不同节点间的关联约束关系,将某种约束条件引入传统的关联规则中,提高大型民航通信系统鲁棒性测试的效率,获取准确的测试结果。实验结果表明,采用所提模型能更精确的分析出航空通信设备的鲁棒性。
Civil aviation communication system belongs to complicated network communication system, avast number of communications node system, complex network robustness analysis algorithm oftraditional test result is distorted. Therefore proposes a hierarchical weight division theory of robustnessanalysis model, and applied to aviation communication system robustness tests, shaping the BP neuralnetwork in large civil communication system robustness evaluation model, the influence of large civilaviation communication system robustness indicators scores, according to the different weighting ofcomposite scores, access to large civil aviation communication system robustness evaluation index ofhierarchical weighted sample test data, according to the obtained large amount of information and thechange of civil aviation communication system, the adaptive weighted weight vector of BP neuralnetwork, establish large associated civil aviation communication between different nodes in the systemconstraints, introduces some constraints in the traditional association rules, improve the efficiency oflarge civil aviation communication system robustness test, to get accurate test results. The experimentalresults show that the proposed model can more accurate analysis of the aviation communicationequipment robustness.
出处
《科技通报》
北大核心
2015年第3期233-235,262,共4页
Bulletin of Science and Technology
关键词
航空通信
复杂网络
鲁棒性
分层权重
aviation communication
complex network
robustness
variable weight
