Network abnormal flow prediction method based on improved radial basis function neural network algorithm
A technology based on neural networks and neural networks, applied in the field of network traffic early warning, can solve problems such as large fluctuations in communication traffic
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[0051] The technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention.
[0052] The embodiment of the present invention proposes a network abnormal traffic prediction method based on the improved radial basis neural network algorithm, which is mainly divided into the following three stages: RBF neural network initialization, optimization of RBF neural network parameters using QAPSO algorithm, and establishment of optimized RBF neural network Network forecasting model and traffic forecasting.
[0053] 1. RBF neural network initialization
[0054] (1) Preprocessing the training data set, generally adopting normalization processing;
[0055] (2) build the structure of RBF neural network: determine input and output, the input and output of the present invention all are the intelligent substation network traffic size based on time series;
[0056] (3) Determine hidden layer nod...
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