基于多层感知器模型的交通预测

O. S. Parra, Gustavo Garcia, B. S. R. Daza
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引用次数: 2

摘要

故障预测的目标是预测网络中的故障,从而能够实时保证服务的可靠性和质量,以保持网络的可用性和可靠性,并启动适当的恢复“正常”的行动。本文介绍了利用人工神经网络多层感知器实现局域网络故障预测系统的过程。介绍了该系统,并对神经网络自身参数的选择、训练算法等进行了测试,并给出了测试结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traffic forecasting using a multi layer perceptron model
The goal of failures forecasting is to predict faults in the network, doing that it is possible to guarantee reliability and quality of service in real time to maintain the network availability and reliability and to initiate appropriate actions of restoration of 'normality'. The following article describes the process performed for implementing failures prediction system in LAN using artificial neural networks multilayer Perceptron. It describes the system, the tests made for the selection of the own parameters of the neural network like the training algorithm and the obtained results.
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