DocumentCode :
1615789
Title :
Analysis and research of several network traffic prediction models
Author :
Xu Lan
Author_Institution :
Coll. of Inf. Sci. & Eng., Bohai Univ., Jinzhou, China
fYear :
2013
Firstpage :
894
Lastpage :
899
Abstract :
There are many factors which affect the prediction of network traffic at present. The traditional network traffic prediction model has not met the needs of prediction. Therefore, many scholars have been researching on the area. This paper analyzed network traffic prediction models based on neural network by ant colony optimization algorithm, based on neural network by quantum particle swarm optimization algorithm, and based on neural network by genetic algorithm optimized; studied the forecasting process of these models; compared the forecasting performance of three models. And proposed view for study in the future.
Keywords :
ant colony optimisation; genetic algorithms; information networks; neural nets; particle swarm optimisation; ant colony optimization algorithm; forecasting process; genetic algorithm; network traffic prediction models; neural network; quantum particle swarm optimization algorithm; Decision support systems; Ant Colony Optimization Algorithm; Genetic Algorithm; Network Traffic; Neural Network; Prediction; Quantum-behaved Particle Swarm Optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Chinese Automation Congress (CAC), 2013
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-0332-0
Type :
conf
DOI :
10.1109/CAC.2013.6775859
Filename :
6775859
Link To Document :
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