Forecasting the server status using the triple exponential smoothing model

Abstract

This article examines the issue of forecasting the time series of server systems and suggests applying the triple exponential smoothing model to solve this problem. It presents a mathematical formulation of the problem and describes the specifics of forecasting the time series of server systems. After this the article gives a comparative analysis of the autoregressive, neural network and exponential smoothing models in terms of their application to this problem. It argues that the triple exponential smoothing model (Holt-Winters method) offers a number of advantages when modelling the time series of server systems. It then provides experimental research to evaluate the accuracy of the Holt-Winters method with respect to the indicated time series. The research shows that the triple exponential smoothing model exhibits high results and can be applied to the solution of practical problems.