用于多媒体网络节点的故障检测仿真

发布时间：2018-05-12 15:14

本文选题：多媒体网络 + 故障检测　；参考：《计算机仿真》2016年08期

【摘要】：对多媒体网络节点的故障进行准确检测,可以有效消除多媒体网络节点故障。在进行多媒体网络节点的故障检测时,需要对多媒体网络节点的状态变化进行动态预测,而传统神经网络的检测方法只能获取多媒体网络节点的静态状态参数,不能实时的对节点状态进行更新与预测,降低了多媒体网络节点故障检测精度。提出一种改进动态灰色预测算法的多媒体网络节点故障检测方法。建立了多媒体网络节点的故障检测模型,融合于灰色预测方法将心跳策略引入到体网络节点的故障检测中,动态地预测出多媒体网络节点的状态变化。利用模糊算法对多媒体网络节点故障信号延迟进行模糊化处理,计算出网络节点的故障观测参数和其参数残差,完成对多媒体网络节点的故障检测。仿真结果证明,改进方法能够有效地提高多媒体网络节点故障检测的准确率。
[Abstract]:The fault detection of multimedia network node can effectively eliminate the fault of multimedia network node. In the fault detection of multimedia network nodes, it is necessary to dynamically predict the state changes of multimedia network nodes, but the traditional neural network detection method can only obtain the static state parameters of multimedia network nodes. The node state can not be updated and predicted in real time, which reduces the accuracy of node fault detection in multimedia network. An improved dynamic grey prediction algorithm for node fault detection in multimedia networks is proposed. The fault detection model of multimedia network nodes is established. The heartbeat strategy is introduced into the fault detection of body network nodes and the state change of multimedia network nodes is dynamically predicted. The fault signal delay of multimedia network node is fuzzed by fuzzy algorithm, and the fault observation parameters and their residuals of network node are calculated, and the fault detection of multimedia network node is completed. Simulation results show that the improved method can effectively improve the accuracy of multimedia network node fault detection.
【作者单位】：北京联合大学商务学院;
【分类号】：TP393.06

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