Network traffic measurement method based on RBF neural network

Abstract

The invention discloses a network traffic measurement method based on an RBF neural network. The network traffic measurement method based on the RBF neural network comprises the following steps in sequence: establishment of an RBF neural network model, normalization processing of network traffic data lines, a learning algorithm of the RBF neural network model, the training algorithm of the RBF neural network model and evaluation of performance of the RBF neural network model. According to the network traffic measurement method based on the RBF neural network, the traffic measurement model based on the RBF neural network is established to give out structural design of the RBF neural network and the learning algorithm based on orthogonal least squares, the RBF method is higher in prediction accuracy relative to a BP traffic prediction model, the RBF method can describe the change rules of network traffic quite well, and has the advantages of being strong in generalization ability and good in stability, and the method has high practical value in network traffic prediction.

Description

【Technical field】 [0001] The invention relates to the technical field of network flow measurement methods, in particular to the technical field of network flow measurement methods based on RBF neural networks. 【Background technique】 [0002] Traffic measurement is the basis for network monitoring, management and control. The Internet is a global network formed by the interconnection of hundreds of millions of computers. With the provision of more network services and the continuous increase of users, network traffic becomes larger and network behavior becomes more and more complex. Although the relevant networking and management technologies are constantly improving, people still don't have a correct and complete understanding of its behavioral characteristics in a local and overall range. Mastering the behavior of the Internet is an important prerequisite for many research work such as network planning, network management and network security, new network protocols and net...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to solve the problems in the prior art, and propose a network flow measurement method based on RBF neural network, which has fast calculation speed and good real-time performance, and has higher approximation ability and good performance compared with traditional linear flow models. Adaptive, and can overcome the shortcomings of long training time and high computational complexity of traffic model based on BP neural network

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