缺失互联网流量数据的插值比较分析

I. D. Irawati, A. B. Suksmono, Ian Joseph Matheus Edward
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引用次数: 1

摘要

在本文中,我们比较了用于修复互联网流量数据缺失的插值技术。这些技术包括二维插值、k近邻(KNN)和相关。我们用缺失概率分别为0.02和0.98来测试各种类型的缺失数据。利用归一化均方误差(NMSE)参数来展示插值技术的性能。仿真结果表明,所有插值方法都具有恢复丢失信息的能力。二维插值和KNN适用于小概率缺失,而相关适用于大概率缺失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Interpolation Comparative Analysis for Missing Internet Traffic Data
In this paper, we compared interpolation techniques for fixing the missing of internet traffic data. These techniques consist of 2-D interpolation, k-nearest neighbors (KNN), and correlation. We test various types of missing data with missing probability of 0.02 and 0.98. The interpolation technique performance is shown using Normalized Mean Square Error (NMSE) parameters. Simulation results show that all interpolation methods have the ability to recover lost information. 2-D interpolation and KNN suitable for small probability of missing while correlation is suitable for large probability of missing.
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