Title :
A short-term prediction for QoS of Web Service based on RBF neural networks including an improved K-means algorithm
Author_Institution :
Sch. of Software, Northeastern Univ., Shenyang, China
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;
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.2010.5620138