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Short-term forecasting model of web traffic based on genetic algorithm and neural network

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1 Author(s)
Meimei Chen ; Dept. of E-Commerce & Logistic, Donghua Univ., Shanghai, China

Network traffic is an important load indicator that reflects the performance of the web system. Short-term forecast of web traffic is the base of effective overload control. Because of the complex and ever-changing network environment, web traffic is shown the characteristics of random and unexpected at most of the time scales. Hence, it is more difficult to improve the accuracy of traffic forecasts to get satisfactory results. In this paper, genetic algorithm is used in artificial neural network to optimize the structure design and weights firstly. Then, a web traffic forecasting model based on genetic neural network is proposed. The simulation result shown that the forecast result of this model is better than that based on BP and Elman neural network prediction model.

Published in:

Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on

Date of Conference:

8-10 Aug. 2011

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