网络可靠性预测模型

Network reliability prediction model

网络可靠性作为系统安全的最基于要求之一,是所有网络信息系统的建设和运行目标。针对采用BP神经网络对网络可靠性建立预测模型,其算法存在收敛速度慢、网络泛化能力差,影响预测精度等缺点。提出采用量子神经网络算法进行网络可靠性预测建模。通过对测试数据进行建模仿真,结果表明,该预测方法较BP神经网络而言,在误差精度,训练次数等方面优于传统神经网络,同时能避免陷入局部极小的缺点,达到了很好的预测效果。

Network reliability is one of the most basic requirements of system security, and it is the goal of the construction and operation of all network information systems. In view of the BP neural network to establish the network reliability prediction model, the algorithm has the shortcomings of slow convergence speed, poor network generalization ability, and impact prediction accuracy. The quantum neural network algorithm is proposed to model the network reliability prediction.Through the modeling and Simulation of the test data. The results show that the prediction method is compared with that of BP neural network, the error precision, the training times and is superior to the traditional neural network, also can avoid falling into local minimum points, to reach a good prediction effect.