Abstract
The article aims to consider least squares approach for solving problems of queuing systems theory. The opportunity of predicting the behavior of infocommunication system is shown. Choosing the optimal model of its functioning is proposed. On base monitoring system metrics, statistical data were formed. The article proposes to make data trend forecasting, to estimate parameters of random processes over time. To obtain the results of functioning data in infocommunication systems that are as close as possible to the real values, polynomial and sine models are considered. The method of regression analysis is proposed to determine the parameter values for a model from a set of observational data. In theoretical research, the linear and nonlinear least squares methods are used in terms of a circle. The task of experimental analysis is to obtain an estimated parameter of sine, polynomial models and the center of circle. Experimental analysis was performed using the mathematical modeling program Matlab. A uniformly distributed random sequence and a random sequence with normal distribution are generated. The sequence with experimental data for polynomial and sine models, respectively, are calculated. The correspondence each model for generated data is shown in graphical form. The measurement data obeys observations. The estimated parameters are summarized in the tables. The polynomial order is estimated. The estimated dispersion curve of the polynomial model is obtained. The calculated variance values of the polynomial model are presented. Data trend forecasting for measurement data is made. The estimated values are extremally close to real data. The results are shown in graphs. Finally, an approximate model of the circumference of measurement data is presented in graphical form. After some iterations with estimated center from the arithmetic mean the new circle center is given. And quite close values for center and radius of circle are obtained.
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