Network flow-predicting method and device based on wavelet package decomposition and fuzzy neural network
A fuzzy neural network and wavelet packet decomposition technology, applied in the field of computer networks, can solve the problems of unreachable prediction, no detailed analysis of high-frequency parts, affecting the accuracy of network traffic prediction, etc.
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[0020] figure 1 A system flow diagram of a specific embodiment of the present invention is shown.
[0021] Step 101: Decompose the original network traffic into wavelets of different time scales through wavelet packet transformation. Wavelet transform theory is a powerful tool for signal analysis and signal processing, and it is a method for analyzing signals from time-frequency domains. Traditional network traffic forecasting algorithms use wavelet decomposition to remove the long-term correlation characteristics of network traffic and realize the decomposition of complex business characteristics of network traffic. Record the network traffic as signal x(t), then its wavelet decomposition can be expressed as:
[0022] x ( t ) = Σ k a Jk φ Jk ( t ) + Σ ...
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