DocumentCode
3075933
Title
Based on Two Swarm Optimized Algorithm of Neural Network to Prediction the Switch´s Traffic of Coal
Author
Shao, Xiao-qiang
Author_Institution
Sch. of Electr. & Control Eng., Xi´´an Univ. of Sci. & Technol., Xi´´an, China
fYear
2011
fDate
16-17 July 2011
Firstpage
299
Lastpage
302
Abstract
Coal accurately predict multi-channel network traffic monitoring network for transmission to enhance and improve the QoS is very important, the characteristics of coalmine monitoring network, the first neural network model was constructed, followed by the ant colony algorithm, on the number of iterations, time, number of parameters such as ants Set, then uses the number of Particle swarm optimization particles, particles and other parameters set the location to complete the layers of neural network weights optimization, simulation by examples of its accuracy.
Keywords
coal; mining industry; neural nets; particle swarm optimisation; process monitoring; quality of service; telecommunication congestion control; telecommunication traffic; QoS; ant colony algorithm; coal mine monitoring network; multichannel network traffic monitoring; neural network; particle swarm optimization; swarm optimized algorithm; switch traffic; Fuzzy neural networks; Mathematical model; Monitoring; Optimization; Particle swarm optimization; Predictive models; Training; Coal; Particle swarm optimization; ant colony algorithm; network traffic;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Society (ISCCS), 2011 International Symposium on
Conference_Location
Kota Kinabalu
Print_ISBN
978-1-4577-0644-8
Type
conf
DOI
10.1109/ISCCS.2011.87
Filename
6004445
Link To Document