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