Neural Networks for Web Server Workload Forecasting

被引：0
作者：
Tran Van Giang
Debusschere, Vincent
Bacha, Seddik
机构：
来源：
2013 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT) | 2013年
关键词：
Neural network; intelligent computational; server workload; data center workload forecasting; EnergeTIC-FUI;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper presents a comparative study of five intelligent forecast models for workload of server defined as HTTP requests. These five forecast models are based on the methodology: Nonlinear AutoRegressive model with eXogenous Inputs (NARX), Multilayer Perceptron (MLP), Elman, Cascade-Neural Network (CCNN) and Pattern Recognition Neural Network (PRNN). The best accuracy prediction is given by the NARX model. This work takes parts in development of our forecast models in the project EnergeTic-FUI, France.
引用
收藏
页码：1152 / 1156
页数：5
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