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电子学报  2012 

小时间尺度网络流量混沌性分析及趋势预测

DOI: 10.3969/j.issn.0372-2112.2012.08.018, PP. 1609-1616

Keywords: 网络流量,趋势预测,混沌理论,最优样本子集,最小二乘支持向量机

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Abstract:

小时间尺度的网络流量的混沌性被噪声掩盖难以预测,本文通过局部投影降噪得到可预测的混沌性流量趋势.针对网络流量存在的时变性和长周期性,提出一种最优样本子集在线模糊最小二乘支持向量机(LeastSquaresSupportVectorMachine,LSSVM)预测方法:以与预测样本时间上以及欧式距离最近的样本点构成最优样本子集,并对其模糊化处理,最后采用模糊LSSVM训练获得预测模型.通过分块矩阵降低预测模型在线更新的运算复杂度.对真实网络流量的降噪以及预测的结果表明本文方法能够快速准确的预测网络流量趋势.

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