网络流量时间序列预测的ANFIS方法

S. Chabaa, A. Zeroual, J. Antari
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引用次数: 23

摘要

本文采用模糊系统与神经网络相结合的自适应神经模糊推理系统(ANFIS)对互联网流量时间序列的输入输出数据进行预测。应用了几个统计标准来证明该模型的有效性。结果表明,从统计指标上看,ANFIS模型在互联网流量预测过程中具有较好的精度。该模型能很好地拟合实际数据,并能有效地描述不同时刻的网络状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ANFIS method for forecasting internet traffic time series
In This paper we have applied the adaptive neuro-fuzzy inference system (ANFIS) which is realized by an appropriate combination of fuzzy systems and neural networks for forecasting a set of input and output data of internet traffic time series. Several statistical criteria are applied to provide the effectiveness of this model. The obtained results demonstrate that the ANFIS model present a good precision in the prediction process of internet traffic in terms of statistical indicators. This model fits well real data and provides an effective description of network condition at different times.
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