Forecasting the Flow of Data Packets for Website Traffic Analysis – ASVR-Tuned ANFIS/NGARCH Approach
Forecast of the flow of data packets between client and server for a website traffic analysis is viewed as a part of web analytics. Thousands of web-smart businesses depend on web analytics to improve website conversions, reduce marketing costs, website optimization, website monitoring and provide a higher level of service to their customers and partners. This paper particularly intends to develop a high-accuracy prediction approach as the need for a website traffic analysis. The proposed composite model (ASVR-ANFIS/NGARCH) is schemed to build a systematic structure such that it is not only to improve the predictive accuracy because of resolving the problems of the overshoot and volatility clustering simultaneously, but also to boost website tracking capacity helping each webmaster to optimize their website, maximize online marketing conversions and lead campaign tracking.
KeywordsData Packet Radial Basis Function Neural Network Composite Model Computer Center Grey Model
Unable to display preview. Download preview PDF.
- 1.Funkhouser, T.A., Sequin, C.H., Teller, S.J.: Management of Large Amounts of Data in Interactive Building Walkthroughs. In: Proc. ACM 0-89791-471-6/92/0003/0011 (1992)Google Scholar
- 2.Aissi, S., Malu, P., Srinivasan, K.: E-business Process Modeling: The Next Big Step. IEEE Computer 35(5), 55–62 (2002)Google Scholar
- 3.Chang, B.R.: Hybrid BPNN-Weighted Grey-CLMS Forecasting. Journal of Information Science and Engineering 21(1), 209–221 (2005)Google Scholar
- 9.Chang, B.R.: Compensation and Regularization for Improving the Forecasting Accuracy by Adaptive Support Vector Regression. International Journal of Fuzzy System 7(3), 109–118 (2005)Google Scholar
- 13.Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines (and other kernel-based learning methods). Cambridge University Press, London (2000)Google Scholar
- 14.Kreyszig, E.: Advanced Engineering Mathematics, 8th edn. Wiley, New York (1999)Google Scholar
- 15.Chang, B.R.: Forecasting the Flow of Data Packets in Web Using ANFISCH Predictor Tuned by Segmented Adaptive Support Vector Regression. In: Proc. The 5th International Conference on Computer and Information Technology, Fudan University, Shanghai, China, September 21-23, 2005, pp. 23–27 (2005)Google Scholar
- 16.Chang, B.R.: Applying Nonlinear Generalized Autoregressive Conditional Heteroscedasticity to Compensate ANFIS Outputs Tuned by Adaptive Support Vector Regression. Fuzzy Sets and Systems 157(13), 1832–1850 (2004)Google Scholar
- 17.Inflow and Outflow of data packets by bits per second in WWW server, computer center, NTTU, http://checknet.nttu.edu.tw:8080/mrtg2/2150.htm
- 18.Inflow and Outflow of data packets by bits per second in WWW server, computer center, STU, http://dcs.stu.edu.tw
- 20.Diebold, F.X.: Elements of Forecasting. South-Western, Cincinnati (1998)Google Scholar