Title :
Reliability prediction of LAN/WLAN integration network based on artificial intelligence
Author :
Xinmei, Liu ; Li, Wang ; Xiaokai, Wang ; Yan, Han
Author_Institution :
Nat. Key Lab. for Electron. Meas. Technol., North Univ. of China, Taiyuan, China
Abstract :
This paper describes the reliability and validation of prediction models of LAN/WLAN integration network. An improved PSO algorithm is used to optimize the weight of BP neural network. Support vector machine (SVM) is used in network reliability prediction. The LAN/WLAN integration network reliability prediction models are established with three methods (BP neural network, improved BP neural network based on PSO, and SVM regression model). The validity of reliability prediction model based on artificial intelligence as well as the advantage of using support vector regression method has also been demonstrated experimentally.
Keywords :
artificial intelligence; backpropagation; neural nets; particle swarm optimisation; regression analysis; support vector machines; telecommunication network reliability; wireless LAN; BP neural network; LAN-WLAN integration network; SVM regression model; artificial intelligence; network reliability prediction; particle swarm optimization; support vector machine; Artificial neural networks; Computer network reliability; Fitting; Reliability; Support vector machines; Testing; Training; artificial intelligence; integration network; reliability prediction;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5622774