Method for predicating long correlation sequences by utilizing short correlation model
A model prediction and long correlation technology, applied in the field of self-similar network traffic prediction, can solve the problems of complex algorithm and low prediction ability, and achieve the effect of high prediction accuracy, reduced complexity and low complexity
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[0033] The technical solutions of the present invention will be further described below in conjunction with specific embodiments.
[0034] Such as figure 1 As shown, the specific embodiment of the present invention is: provide a kind of method utilizing short correlation model to predict long correlation sequence, comprise the steps:
[0035] Step 100: Decompose the self-similar network traffic, that is, take the maximum and minimum points of the signal x(t) to be analyzed and fit them with two cubic spline curves to obtain the upper and lower extremes of x(t) Value envelope, use m(t) to represent the average value of the two envelopes, let h(t)=x(t)-m(t), if the number of h(t) signal extreme points is the same as the zero-crossing point The numbers must be equal or differ by at most one, and at any point in time, the mean value of the envelope defined by the local maximum and local minimum of the h(t) signal is zero, then h(t) is the first IMF, otherwise Treat h(t) as x(t),...
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