DocumentCode :
532206
Title :
A short-term prediction for QoS of Web Service based on RBF neural networks including an improved K-means algorithm
Author :
Zhang Jin-hong
Author_Institution :
Sch. of Software, Northeastern Univ., Shenyang, China
Volume :
5
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
The structure of RBF neural networks and an improved K-means algorithm will be introduced in the paper. Based on this, RBF neural networks is applied to predict the QoS of Web Service and the functions of the MATLAB toolbox are adopted to create a network model for QoS prediction. Finally the simulation experiments will prove that using RBF neural networks based on the improved K-means algorithm to predict the QoS of Web Service is effective and efficient.
Keywords :
Web services; mathematics computing; pattern clustering; quality of service; radial basis function networks; MATLAB toolbox; QoS; RBF neural networks; k-means algorithm improvement; short term prediction; web service; Annealing; Artificial neural networks; Computer languages; Improved K-Means Algorithm; QoS Prediction; QoS Weight; RBF Neural Networks; Web Service;
fLanguage :
English
Publisher :
ieee
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
Type :
conf
DOI :
10.1109/ICCASM.2010.5620138
Filename :
5620138
Link To Document :
بازگشت