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Fault Diagnosis of Computer Network Based on Rough Sets and BP Neural Network

机译:基于粗糙集和BP神经网络的计算机网络故障诊断。

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Abstract-A new fault diagnosis model of computer network based on rough set and BP neural network is put forward in this paper. Many fault features of computer network are retrieved, then they are reduced to the minimum diagnosis rules by rough set. And the minimum diagnosis rules are trained by BP neural network. The simulation results indicate that the new fault diagnosis model has higher learning efficiency, faster speed of diagnosis and higher diagnosis accuracy. It can find the types and the locations of computer network faults quickly and accurately.
机译:摘要-提出了一种基于粗糙集和BP神经网络的计算机网络故障诊断模型。检索计算机网络的许多故障特征,然后通过粗糙集将它们减少到最小诊断规则。最低诊断规则由BP神经网络训练。仿真结果表明,新的故障诊断模型具有较高的学习效率,更快的诊断速度和更高的诊断精度。它可以快速,准确地找到计算机网络故障的类型和位置。

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